125 Azure Ai Jobs

Exp: 2-3 years Skills : Proficiency in languages Python, C#,net, Prompt engineering, knowledge of the Azure AI Foundry projects, Azure OpenAI, Azure AI Search

Job Title: Azure Cloud Engineer Location: Bangalore Experience: 5-8 years Notice- Immediate to 30 days. Contact : 9258253740 Role Overview We are seeking a skilled Azure Cloud Engineer with deep expertise in designing, deploying, and managing cloud infrastructure on Microsoft Azure. The ideal candidate will be proficient in Terraform , experienced in Power Automate setup and licensing, and well-versed in Azure AI services . This role demands hands-on technical leadership and collaboration across cross-functional teams. Key Responsibilities Azure Resource Management Deploy and configure Azure services: VMs, App Services, Storage, Networking, Databases, AI/ML Manage identity and access using Azure AD and RBAC Ensure secure, cost-effective deployments across Dev/Test/Prod Infrastructure as Code (IaC) Design and maintain infrastructure using Terraform Automate provisioning and scaling of cloud resources Maintain version-controlled IaC repositories Power Automate & Licensing Build and manage Power Automate flows Advise on licensing tiers and recommend optimal plans Integrate flows with Azure and third-party platforms Azure AI & Innovation Deploy and manage services like Azure OpenAI, Cognitive Services, Document Intelligence, AI Search, Azure ML Collaborate with Data Science teams to scale AI workloads Security & Monitoring Implement security best practices, private endpoints, and managed identities Monitor resources using Azure Monitor, Log Analytics, and Application Insights Ensure compliance with internal and industry standards Collaboration & Support Partner with DevOps, Data Science, and App Development teams Provide documentation, training, and technical support Qualifications Education Bachelors in Computer Science, IT, or related field (or equivalent experience) Experience Minimum 5 years of hands-on Azure experience Proven track record in cloud architecture and deployment Technical Skills Azure resource setup and management Terraform or equivalent IaC tools (Bicep, ARM templates) Power Automate setup, licensing, and integration CI/CD pipelines (Azure DevOps, GitHub Actions) Networking, security, and governance in Azure Certifications (Preferred) AZ-104: Azure Administrator Associate AZ-305: Azure Solutions Architect Expert AI-102: Azure AI Engineer Associate Soft Skills Strong problem-solving and troubleshooting abilities Excellent communication and stakeholder engagement

Agentic AI Project Manager Microsoft Initiatives C2 Job Description We are seeking a dynamic and technically fluent Project Manager to lead the delivery of Agentic AI initiatives within the Microsoft ecosystem. This role will oversee the planning, execution, and scaling of AI solutions that leverage Microsoft technologies such as Azure AI Agent Service, Power Platform, Semantic Kernel, and Copilot Studio. The ideal candidate will combine agile delivery expertise with a strong understanding of AI orchestration frameworks and enterprise compliance. Responsibilities Program Management & Delivery Lead end-to-end delivery of Agentic AI projects, from ideation and PoC to deployment and scaling across Microsoft platforms. Manage project scope, timelines, budgets, and risks while ensuring alignment with business goals and technical feasibility Microsoft AI Ecosystem Integration Coordinate the implementation of Microsoft-native AI components including Azure AI Foundry, Power Automate, and Copilot integrations. Ensure solutions are compliant with Microsoft’s Responsible AI principles, including cost optimization, bias detection, and audit workflows Stakeholder Engagement Act as the primary liaison between business stakeholders, technical teams, and Microsoft partners. Facilitate workshops, demos, and governance reviews to ensure stakeholder alignment and transparency Agile Execution & Governance Apply Agile/Scrum methodologies to manage sprints, backlogs, and iterative delivery cycles. Track KPIs, manage change requests, and ensure documentation and audit readiness. Innovation & Reusability Promote reuse of accelerators, templates, and frameworks across AI projects. Contribute to the development of delivery playbooks and best practices for Microsoft Agentic AI programs Required Skills & Qualifications Bachelor's / Masters degree in computer science, Engineering, Mathematics, Statistics, or related field Proven experience managing AI/ML or GenAI projects, ideally within Microsoft environments. Strong understanding of Microsoft AI stack: Azure AI, Power Platform, Microsoft Copilot, and Semantic Kernel. Familiarity with orchestration frameworks like LangChain, LangGraph, or AutoGen is a plus. Experience in managing deploying activities with Gen AI stack/services provided by various platforms such as AWS, GCP, Azure Experience in project management for AI/ML, Generative AI and Agentic AI Projects. Excellent communication, stakeholder management, and cross-functional leadership skills. PMP, PRINCE2, or Agile certifications preferred. Collaborate with data engineers, data scientists, and business stakeholders to understand the data and the business problems.

As a Platform Development and Machine Learning expert at Adobe, you will play a crucial role in changing the world through digital experiences by building scalable AI platforms and designing ML pipelines. Your responsibilities will include: - Building scalable AI platforms that are customer-facing and evangelizing the platform with customers and internal stakeholders. - Ensuring platform scalability, reliability, and performance to meet business needs. - Designing ML pipelines for experiment management, model management, feature management, and model retraining. - Implementing A/B testing of models and designing APIs for model inferencing at scale. - Demonstrating proven expertise with MLflow, SageMaker, Vertex AI, and Azure AI. - Serving as a subject matter expert in LLM serving paradigms and possessing deep knowledge of GPU architectures. - Expertise in distributed training and serving of large language models and proficiency in model and data parallel training using frameworks like DeepSpeed and service frameworks like vLLM. - Demonstrating proven expertise in model fine-tuning and optimization techniques to achieve better latencies and accuracies in model results. - Reducing training and resource requirements for fine-tuning LLM and LVM models. - Having extensive knowledge of different LLM models and providing insights on the applicability of each model based on use cases. - Delivering end-to-end solutions from engineering to production for specific customer use cases. - Showcasing proficiency in DevOps and LLMOps practices, including knowledge in Kubernetes, Docker, and container orchestration. - Deep understanding of LLM orchestration frameworks like Flowise, Langflow, and Langgraph. Your skills matrix should include expertise in LLM such as Hugging Face OSS LLMs, GPT, Gemini, Claude, Mixtral, Llama, LLM Ops such as ML Flow, Langchain, Langraph, LangFlow, Flowise, LLamaIndex, SageMaker, AWS Bedrock, Vertex AI, Azure AI, Databases/Datawarehouse like DynamoDB, Cosmos, MongoDB, RDS, MySQL, PostGreSQL, Aurora, Spanner, Google BigQuery, Cloud Knowledge of AWS/Azure/GCP, Dev Ops knowledge in Kubernetes, Docker, FluentD, Kibana, Grafana, Prometheus, and Cloud Certifications (Bonus) in AWS Professional Solution Architect, AWS Machine Learning Specialty, Azure Solutions Architect Expert. Proficiency in Python, SQL, and Javascript is also required. Adobe is committed to creating exceptional employee experiences and values diversity. If you require accommodations to navigate the website or complete the application process, please contact accommodations@adobe.com or call (408) 536-3015.,

Agentic AI Solutions Architect (Microsoft & Copilot) Role Title: Agentic AI Solutions Architect (Microsoft & Copilot) Location : [Pan India] Your Role: As an Agentic Solutions Architect specializing in Microsoft technologies, this role involves leading the design and implementation of enterprise-grade Agentic AI solutions that leverage the comprehensive Microsoft ecosystem. The architect translates complex business challenges into robust, scalable, and secure architectures, thereby driving digital transformation through the deployment of autonomous AI agents. Expertise in ensuring compliance, optimizing performance, and facilitating seamless integration within hybrid and multi-cloud environments, utilizing Microsoft's advanced AI, 365, Power Platform and Azure offerings, is paramount. Your work will center on developing, configuring, and maintaining AI agents using Microsoft Copilot Studio, ensuring they align with design specifications and deliver tangible value. This position requires a deep understanding of Microsofts approach to AI-enabled delivery, ensuring that solutions embed controls for cost containment, bias detection, model traceability, explainability, and audit workflows. The architect will advise clients on how to tailor Microsoft Agentic AI platform components to meet specific domain, regulatory, or technical requirements, ensuring that solutions are not only innovative but also practical and compliant. Your Tasks: The Agentic Solutions Architect (Microsoft) leads the technical planning, design, and integration of Agentic AI solutions within the Microsoft Azure ecosystem, specifically focusing on Power Platform, Azure AI Foundry, Azure AI Agent Service, Copilot Studio, and Semantic Kernel. This includes designing reference architectures and solution blueprints that embed Responsible AI controls, such as cost containment, bias detection, traceability, explainability, and audit workflows, while ensuring compliance with evolving AI regulations. The architect advises business units and client teams on tailoring Microsoft Agentic AI platform components to meet specific domain, regulatory, or technical requirements. Collaboration with delivery and IT teams is essential to ensure system compatibility, performance, and security of Agentic AI components, aligning with broader enterprise architecture and data governance strategies. The architect also contributes to pre-sales efforts and client-facing enablement as a subject matter expert in Microsoft Agentic AI implementation, articulating solution value and building technical confidence. A key responsibility involves leading solution design for generative technologies, including effort estimation, pricing, and business case presentations for clients, clearly demonstrating the return on investment. The architect identifies opportunities for transformation, automation, and AI adoption within client organizations, leveraging Microsoft's capabilities. Your Profile (needed): Candidates must possess significant experience (3+ years) in data & automation solution architecture, with proven successes focused on Generative AI and/or Agentic AI solutions. Proven experience in leading solution design for generative technologies, including effort estimation, pricing, and business case presentations for clients, is essential. Deep hands-on expertise with Microsoft Azure AI services, particularly Azure AI Foundry, Azure AI Agent Service, Microsoft Copilot Studio, and Semantic Kernel, is required. Strong experience in opportunity identification for transformation, automation, and AI within enterprise environments is also necessary. A working knowledge of cloud architectures (AWS, GCP, Azure), enterprise integration patterns, and DevOps practices is expected. Strong grasp of advanced AI concepts, including multi-agent workflows, reasoning & decision engines, and autonomous agent design, is critical. Your Profile (nice to have): Prior knowledge of Power Platform is a significant value add. Knowledge of Model Context Protocol (MCP) and Agent-to-Agent (A2A) protocols is highly desirable. Experience with rapid prototyping of Generative and Agentic AI solutions would be beneficial. Familiarity with Microsoft, SAP, and Oracle suites and their integration with AI is a plus. Experience with AI safety testing frameworks is valuable. A consulting background or prior experience in a client-facing technical specialist role would be advantageous.

We are seeking highly skilled and innovative Data Scientists with strong expertise in Azure AI and ML to join our team. The ideal candidates will bring deep experience in building and deploying advanced machine learning and AI models, particularly working with unstructured data, NLP, and generative AI solutions. You will play a key role in designing, experimenting, and delivering AI-driven capabilities that unlock business value and innovation. Key Responsibilities Design, develop, and deploy ML and AI models on the Azure ecosystem. Work extensively with unstructured data sets (text, images, documents, etc.) to extract insights and build scalable solutions. Apply advanced Natural Language Processing (NLP) and Natural Language Generation (NLG) techniques to solve business problems. Leverage Copilot Studio, AI Foundry, Genie AI in Databricks , and other Azure-native services for generative AI use cases. Collaborate with cross-functional teams to identify AI opportunities and deliver impactful solutions. Continuously explore, test, and implement new algorithms, tools, and frameworks to improve model accuracy and performance. Communicate findings and recommendations effectively to both technical and non-technical stakeholders. Take ownership and accountability for end-to-end project delivery, from data exploration to production deployment. Required Skills & Qualifications Proven hands-on experience in Azure Machine Learning, Azure AI services, and Databricks . Strong background in NLP, NLG, LLMs, and generative AI frameworks . Experience with unstructured data pipelines and feature engineering. Proficiency in Python, PySpark, and ML libraries (TensorFlow, PyTorch, Hugging Face, etc.). Practical experience with Copilot Studio, AI Foundry, Genie AI in Databricks is highly desirable. Strong problem-solving, analytical, and innovation skills. Excellent communication and storytelling ability to present AI solutions to stakeholders. Bachelors or Masters degree in Computer Science, Data Science, AI/ML, or related field. Preferred Qualifications Experience in building and deploying enterprise-grade AI solutions in cloud-native environments. Prior exposure to GenAI-based copilots, conversational AI, or knowledge assistants . Familiarity with MLOps frameworks for productionizing AI models. Show more Show less

Senior Data Scientist Location : Bangalore Mode: Hybrid Job Description We are seeking highly skilled and innovative Data Scientists with strong expertise in Azure AI and ML to join our team. The ideal candidates will bring deep experience in building and deploying advanced machine learning and AI models, particularly working with unstructured data, NLP, and generative AI solutions. You will play a key role in designing, experimenting, and delivering AI-driven capabilities that unlock business value and innovation. Key Responsibilities: Design, develop, and deploy ML and AI models on the Azure ecosystem. Work extensively with unstructured data sets (text, images, documents, etc.) to extract insights and build scalable solutions. Apply advanced Natural Language Processing (NLP) and Natural Language Generation (NLG) techniques to solve business problems. Leverage Copilot Studio, AI Foundry, Genie AI in Databricks, and other Azure-native services for generative AI use cases. Collaborate with cross-functional teams to identify AI opportunities and deliver impactful solutions. Continuously explore, test, and implement new algorithms, tools, and frameworks to improve model accuracy and performance. Communicate findings and recommendations effectively to both technical and non-technical stakeholders. Take ownership and accountability for end-to-end project delivery, from data exploration to production deployment. Required Skills & Qualifications Proven hands-on experience in Azure Machine Learning, Azure AI services, and Databricks. Strong background in NLP, NLG, LLMs, and generative AI frameworks. Experience with unstructured data pipelines and feature engineering. Proficiency in Python, PySpark, and ML libraries (TensorFlow, PyTorch, Hugging Face, etc.). Practical experience with Copilot Studio, AI Foundry, Genie AI in Databricks is highly desirable. Strong problem-solving, analytical, and innovation skills. Excellent communication and storytelling ability to present AI solutions to stakeholders. Bachelors or Masters degree in Computer Science, Data Science, AI/ML, or related field. Preferred Qualifications Experience in building and deploying enterprise-grade AI solutions in cloud-native environments. Prior exposure to GenAI-based copilots, conversational AI, or knowledge assistants. Familiarity with MLOps frameworks for productionizing AI models. Show more Show less

Key Responsibilities Pre-Sales & Client Engagement Act as the AI subject matter expert in client conversations, workshops, and solution envisioning sessions. Support proposal development, architecture documentation, and effort estimation for AI projects. Translate complex business needs into high-level and detailed technical architecture diagrams and blueprints. Design Azure AI Solutions Define architectural patterns for integrating LLMs, generative AI, RAG pipelines, vector databases (e.g., Azure AI Search, FAISS), and orchestration frameworks (e.g., Semantic Kernel, LangChain). Support team in building Azure Cost estimates for various types of solution archetypes, provide guidance on selecting the most cost-effective Azure AI service configurations (e.g., model size, region, compute SKUs). Ensure scalability, security, governance, and compliance are foundational in all designs. Copilot Extension & Customization Provide subject matter expertise in using Azure AI Studio to extend and fine-tune Microsoft 365 Copilots and custom business Copilots. Integrate enterprise data and logic to create domain-specific copilots aligned with customer workflows. Apply prompt engineering and grounding strategies to enhance context awareness and action-taking capabilities. Advanced AI Pipeline Development Build retrieval-augmented generation (RAG) pipelines and advanced RAG pipelines (such as GraphRAG) using Azure AI Search, Cognitive Search, and Semantic Kernel. Design chunking, embedding, ranking, and post-processing strategies to optimize search relevance and model responses. Connect unstructured and structured content (e.g., PDFs, Word, Excel, D365 data) to GenAI models for personalized search and Q&A. Leverage Azure Custom Skills to enrich data across the pipeline to build enterprise-grade scaled AI solutions AI Agent Design and Orchestration Design and deploy multi-step AI agents that reason, retrieve, and take action based on dynamic workflows. Develop solution archetypes (e.g., knowledge assistants, workflow copilots, policy advisors) powered by Semantic Kernel or Azure OpenAI Function Calling. Implement agent memory, state management, and tool integration (APIs, plugins, functions). AI Lifecycle Engineering Automate deployment using Azure DevOps, CI/CD, and containerization where needed. Monitor model outputs for relevance, accuracy, and alignment to responsible AI principles. Collaborate with data engineers, solution architects, and UX designers for full-stack deployment. Technical Leadership & Delivery Oversight Provide technical leadership on AI implementations, including model training, inferencing, and MLOps integration. Conduct architecture reviews, code walkthroughs, and design governance. Collaboration and Communication Collaborate cross-functionally (software engineering, product, design, etc.) to align AI solutions with business goals. Document and communicate technical designs, roadmaps, and updates to both technical and non-technical stakeholders. Research and Innovation Stay current on emerging AI/ML and Generative AI trends, frameworks, and tools, recommending advancements that can enhance our AI initiatives. Champion a culture of continuous learning and experimentation across the organization. Qualifications Education: Bachelor s or Master s degree in Computer Science, Engineering, Mathematics, or a related field (or equivalent experience). Experience: 5+ years of hands-on AI/ML engineering experience, with a strong focus on Microsoft Azure. Proven experience with Generative AI models (LLMs, text or image generation) is highly desirable. Required Skills: 5+ years of experience in AI/ML solution engineering, with a focus on Microsoft Azure AI services. Proficient with: Azure AI Studio, Azure OpenAI Service, Azure Cognitive Search / AI Search Semantic Kernel, LangChain (preferred), or similar orchestration frameworks Prompt engineering, grounding techniques, embedding models Experience building RAG-based applications and deploying GenAI models in production. Strong Python and/or C# skills for SDK use and orchestration logic. Familiarity with REST APIs, Azure Functions, and plugin development. Azure certifications (e.g., Azure AI Engineer Associate, Solutions Architect). Experience with Copilot Studio, Graph RAG, or Microsoft Fabric integrations. Knowledge of Responsible AI, prompt safety, and guardrail implementation. Nice to have skills: Soft Skills: Excellent problem-solving and analytical abilities. Strong communication and collaboration skills. Ability to work in a fast-paced, agile environment, managing multiple priorities effectively.

You will be responsible for analyzing and transforming complex datasets into actionable insights using Microsoft Fabric, Power BI, and AI/ML tools. You will also be tasked with building predictive and prescriptive models by leveraging Azure AI, OpenAI, and other advanced technologies. Collaboration with Platform Engineers and Full Stack Developers to ensure seamless integration of data pipelines and analytics will be a key aspect of your role. Your duties will include designing and maintaining scalable data models that drive decision-making across organizations. Additionally, you will be expected to develop visually compelling dashboards and reports tailored for business leaders. It is crucial to stay informed about AI and analytics trends, while proactively identifying opportunities for innovation. Furthermore, as part of your responsibilities, you will need to present key findings to stakeholders, translating complex analytics into clear, actionable business strategies. Given the direct client interaction involved in this role, strong communication skills are essential. ,

Required Qualifications & Experience Education: Bachelor s or Master s degree in Computer Science, Engineering, or a related field. Advanced degrees or relevant certifications (e.g. in AI/ML or Enterprise Architecture) are a plus. Experience: Approximately8-10 years of experienceworking with cutting-edge technologies in enterprise environments r . This should include hands-on architecture or development of AI/ML solutions, intelligent automation, and systems integration projects. Prior roles could be in solution architecture, innovation labs, or enterprise architecture functions. AI/ML Expertise: background in artificial intelligence and machine learning. Experience designing or implementing solutions such as predictive analytics, natural language processing,conversational AI (chatbots), orgenerative AIapplications. Familiarity with AI frameworks (TensorFlow, PyTorch) and AI cloud services (Azure AI, Google Vertex AI, AWS ML services, etc.). Automation & Integration: Proven experience with enterprise automation tools and integration techniques. This may include RPA platforms (e.g. UiPath, Automation Anywhere), workflow automation, business process management suites, or custom scripting to integrate systems. Ability to design integrations via APIs, ETL pipelines, message queues, or middleware to connect heterogeneous systems. Enterprise Systems Knowledge: Broad understanding of enterprise application landscapes - for example, experience working with or integratingSaaS platformslike ServiceNow (ITSM workflows), Salesforce (CRM), Workday (HRIS), Oracle or SAP (ERP), and industry-specific systems (such as EHRs in healthcare). Able to quickly learn new platforms capabilities and constraints to design compatible innovative solutions. Architecture & Security Acumen: Deep knowledge of enterprise architecture principles and design patterns. Familiarity with architecture frameworks (TOGAF or similar) and cloud architecture best practices.Experience navigating architecture governance, compliance, and data security in large organizations- e.g. understanding data protection policies, identity and access management, network security basics, and regulatory constraints that affect solution design. Project Leadership: Demonstrated ability to lead technology projects or innovation initiatives end-to-end. Skilled in agile project management and comfortable overseeing fast-paced prototype development. Able to coordinate cross-functional teams (developers, analysts, UX, etc.) and external vendors if required. Communication & Stakeholder Management: Excellent client-facing communication skills. Proven ability toengage with both technical and non-technical stakeholders - from engineering teams to C-suite executives. Strong presentation and storytelling skills to articulate vision and technical concepts in business terms. Experience inmanaging stakeholder expectations and securing buy-in for new ideas. Problem-Solving & Innovation Mindset: A creative thinker who stays updated on emerging tech trends. Passion for experimenting with new tools and approaches. Comfortable with a fail-fast mindset to quickly prototype, learn, and iterate. Strong analytical and problem-solving skills to devise innovative solutions to complex business problems. Adaptability: Experience working in ambiguous, evolving environments. Ability to adapt to different industries and client contexts quickly. Enthusiasm for continuous learning and upskilling in fast-moving technology domains.

Required Qualifications & Experience Education: Bachelor s or Master s degree in Computer Science, Engineering, or a related field. Advanced degrees or relevant certifications (e.g. in AI/ML or Enterprise Architecture) are a plus. Experience: Approximately8-10 years of experienceworking with cutting-edge technologies in enterprise environments r . This should include hands-on architecture or development of AI/ML solutions, intelligent automation, and systems integration projects. Prior roles could be in solution architecture, innovation labs, or enterprise architecture functions. AI/ML Expertise: background in artificial intelligence and machine learning. Experience designing or implementing solutions such as predictive analytics, natural language processing,conversational AI (chatbots), orgenerative AIapplications. Familiarity with AI frameworks (TensorFlow, PyTorch) and AI cloud services (Azure AI, Google Vertex AI, AWS ML services, etc.). Automation & Integration: Proven experience with enterprise automation tools and integration techniques. This may include RPA platforms (e.g. UiPath, Automation Anywhere), workflow automation, business process management suites, or custom scripting to integrate systems. Ability to design integrations via APIs, ETL pipelines, message queues, or middleware to connect heterogeneous systems. Enterprise Systems Knowledge: Broad understanding of enterprise application landscapes - for example, experience working with or integratingSaaS platformslike ServiceNow (ITSM workflows), Salesforce (CRM), Workday (HRIS), Oracle or SAP (ERP), and industry-specific systems (such as EHRs in healthcare). Able to quickly learn new platforms capabilities and constraints to design compatible innovative solutions. Architecture & Security Acumen: Deep knowledge of enterprise architecture principles and design patterns. Familiarity with architecture frameworks (TOGAF or similar) and cloud architecture best practices.Experience navigating architecture governance, compliance, and data security in large organizations- e.g. understanding data protection policies, identity and access management, network security basics, and regulatory constraints that affect solution design. Project Leadership: Demonstrated ability to lead technology projects or innovation initiatives end-to-end. Skilled in agile project management and comfortable overseeing fast-paced prototype development. Able to coordinate cross-functional teams (developers, analysts, UX, etc.) and external vendors if required. Communication & Stakeholder Management: Excellent client-facing communication skills. Proven ability toengage with both technical and non-technical stakeholders - from engineering teams to C-suite executives. Strong presentation and storytelling skills to articulate vision and technical concepts in business terms. Experience inmanaging stakeholder expectations and securing buy-in for new ideas. Problem-Solving & Innovation Mindset: A creative thinker who stays updated on emerging tech trends. Passion for experimenting with new tools and approaches. Comfortable with a fail-fast mindset to quickly prototype, learn, and iterate. Strong analytical and problem-solving skills to devise innovative solutions to complex business problems. Adaptability: Experience working in ambiguous, evolving environments. Ability to adapt to different industries and client contexts quickly. Enthusiasm for continuous learning and upskilling in fast-moving technology domains.

As an AI Business Analyst at AskGalore, your primary responsibility will be to bridge the gap between business needs and AI solutions. You will collaborate with key stakeholders to understand business challenges, identify opportunities for AI solutions, and gather requirements. It will be your duty to translate these business requirements into AI system functionalities, which includes data inputs, processing, and expected outputs. You will also be required to develop clear and detailed business analysis documents, such as workflows, use cases, and user stories. In the realm of AI Solution Design & Development, you will work closely with data scientists and AI developers to ensure alignment between business needs and the AI models being developed. Your involvement in the design of AI models will ensure that business logic, data flows, and key metrics are appropriately incorporated. Furthermore, you will assist in identifying the right AI technologies and frameworks based on project needs. Data Analysis & Interpretation will also be a crucial aspect of your role. You will analyze complex datasets to identify trends, insights, and opportunities for AI implementation. Collaboration with data engineers will be necessary to ensure proper data collection, cleaning, and validation for AI model development. Additionally, you will help refine AI models based on feedback and performance analysis. Project Management will fall under your purview as you manage the end-to-end lifecycle of AI projects, ensuring alignment with business goals and timelines. Communication facilitation between business stakeholders, AI teams, and technical developers will be essential for successful project delivery. Monitoring project progress, resolving issues, and ensuring project milestones are achieved on time will be part of your responsibilities. In the domain of AI Solution Deployment & Support, you will support the deployment of AI solutions and ensure their proper integration with business processes. Training users on AI-powered tools and solutions, providing necessary documentation and support for adoption will also be key. Monitoring post-implementation performance of AI systems, collecting feedback, and facilitating any adjustments or optimizations will ensure continuous improvement. Additionally, you will be expected to stay informed on AI trends, emerging technologies, and best practices through Market & Industry Research. Conducting competitive analysis and benchmarking will enable you to identify how AI can improve operational efficiency or customer experience. As an ideal candidate, you should possess a Bachelor's or Master's degree in Business Administration, Data Science, Information Systems, Computer Science, or a related field. With 2-5 years of experience in business analysis, data analytics, or a similar role, along with experience in AI, machine learning, or data science projects, you will be well-equipped for this position. Strong technical skills in AI/ML concepts, algorithms, data analysis tools (e.g., SQL, Python, R), visualization tools (e.g., Power BI, Tableau), and familiarity with AI platforms (e.g., TensorFlow, Azure AI, Google AI) will be advantageous. Excellent problem-solving skills, strong project management skills, and the ability to create clear documentation, workflows, and presentations are essential. Your key competencies will include analytical thinking, strong communication skills, problem-solving abilities, and effective project management capabilities. Join AskGalore and be part of a dynamic team where innovation meets excellence. If you are passionate about AI and ready to lead impactful projects, we encourage you to apply and contribute to the future of digital innovation with us.,

AI Sales Expert Hyderabad, TG Full Time role Salary: DOE Will sponser L1 Visa Job Summary: We are seeking a highly motivated and experienced AI Sales Expert to drive the growth of our AI business by identifying opportunities, pitching innovative AI solutions, and closing deals with enterprise and mid-market clients. This role combines deep understanding of AI technologies with a strong sales acumen to articulate value-driven AI use cases tailored to specific industries. Key Responsibilities: Lead generation & business development: Identify, qualify, and nurture leads for AI-related services and products. Consultative sales: Understand client pain points and pitch relevant AI-based solutions (e.g., automation, NLP, computer vision, ML models). Proposal development: Collaborate with pre-sales and technical teams to craft compelling proposals, solution architectures, and pricing models. Client engagement: Act as a trusted advisor for clients, guiding them through the discovery, evaluation, and implementation phases. Pitching & presentations: Deliver persuasive pitches and demos tailored to C-level executives, stakeholders, and technical teams. Sales pipeline management: Own and manage the AI sales pipeline using CRM tools; regularly report on progress and forecasts. Market intelligence: Stay up-to-date with trends in AI and emerging technologies to tailor offerings and anticipate market needs. Partnership building: Foster relationships with key technology partners, vendors, and system integrators to enable strategic collaborations. Required Qualifications: Proven track record in B2B tech sales, ideally in AI/ML, SaaS, or enterprise software. Deep understanding of AI technologies (e.g., generative AI, machine learning, LLMs, predictive analytics). Strong consultative selling skills with ability to translate technical solutions into business value. Excellent communication and presentation skills. Ability to work with cross-functional teams including product managers, data scientists, and developers. Bachelors degree in Business, Computer Science, Engineering, or related field; MBA is a plus. Preferred Skills: Experience selling AI services to industries such as healthcare, finance, retail, or manufacturing. Familiarity with AI platforms and tools (e.g., Azure AI, AWS SageMaker, Google Vertex AI, OpenAI APIs). Existing network of enterprise clients or C-level decision-makers. Ability to write compelling RFP responses and case studies. KPIs / Success Metrics: Number of qualified leads generated per quarter. Conversion rate from lead to closed deals. Total revenue generated from AI projects. Customer satisfaction and retention post-sale. Growth of AI sales pipeline and market share. Show more Show less

You are a highly skilled and motivated Software Engineer with expertise in Azure AI, Cognitive Services, Machine Learning, and IoT. Your role involves designing, developing, and deploying intelligent applications utilizing Azure cloud technologies, AI-driven solutions, and IoT infrastructure to drive business innovation and efficiency. Your responsibilities include developing and implementing AI-driven applications using Azure AI and Cognitive Services, designing and deploying machine learning models for automation and decision-making, integrating IoT solutions with cloud platforms for real-time data processing, collaborating with cross-functional teams to architect scalable, secure, and high-performance solutions, optimizing AI models for accuracy and cost-effectiveness, ensuring best practices in cloud security, data governance, and compliance, monitoring and troubleshooting AI and IoT solutions in production environments, and staying updated with the latest advancements in AI, ML, and IoT technologies. You hold a Bachelors or Masters degree in Computer Science, Engineering, or a related field. Your skills include strong experience with Azure AI, Cognitive Services, and Machine Learning, proficiency in IoT architecture and data processing using Azure IoT services, expertise in deploying and managing machine learning models in cloud environments, understanding of RESTful APIs, microservices, and cloud-native application development, experience with DevOps practices, CI/CD pipelines, and containerization, knowledge of cloud security principles, and excellent problem-solving abilities in an agile development environment. Preferred qualifications include certifications in Microsoft Azure AI, IoT, or related cloud technologies, experience with Natural Language Processing (NLP) and Computer Vision, familiarity with big data processing and analytics tools, and prior experience in deploying edge computing solutions.,

In this job, I am accountable for: Identifying operational improvements and finding solutions by applying CI tools and techniques Responsible for completing tasks and transactions within agreed KPI's Knows and applies fundamental work theories/concepts/processes in own areas of work Engaging with business & functional partners to understand business priorities, ask relevant questions and scope same into a analytical solution document calling out how application of data science will improve decision making In depth understanding of techniques to prepare the analytical data set leveraging multiple complex data set sources Building Statistical models and ML algorithms with practitioner level competency Writing structured, modularized & codified algorithms using Continuous Improvement principles (development of knowledge assets and reusable modules on GitHub, Wiki, etc) with expert competency Building easy visualization layer on top of the algorithms in order to empower end-users to take decisions - this could be on a visualization platform (Tableau / Python) or through a recommendation set through PPTs Working with the line manager to ensure application / consumption and also think beyond the immediate ask and spot opportunities to address the bigger business questions (if any) Experience relevant for this job: - Applied Math: Applied Statistics, Design of Experiments, Linear -1-2 year experience in data science application in Retail or CPG & Logistic Regression, Decision Trees, Forecasting, Optimization Preferred algorithms - Functional experience: Marketing, Supply Chain, Customer, - Tech: SQL, Hadoop, Python, Tableau, MS Excel, MS Merchandising, Operations, Finance or Digital Powerpoint - Soft Skills: Analytical Thinking & Problem solving, Storyboarding

We are seeking an Automation & Digitalization Manager for the Global Competency Services (GCS) to spearhead the strategy, development, and execution of automation and digital transformation initiatives. In this pivotal role, you will be instrumental in driving operational efficiency, streamlining processes, and harnessing advanced technologies like AI, ML, PBI, Power app, power automate, VBA, SAP Scripting, Web application, and data analytics to optimize business functions and elevate decision-making prowess. Your key responsibilities will include identifying, creating, and implementing automation solutions utilizing cutting-edge tools such as AI, ML, PBI, Power app, power automate, VBA, SAP Scripting, Web application to enhance operational effectiveness. You will be responsible for driving process optimization and workflow automation across various functions like procurement, supply chain, sales, and customer service. Collaboration with business stakeholders to comprehend challenges and architect scalable automation frameworks will be pivotal. Additionally, you will lead the charge in formulating the digitalization strategy for GCS by integrating novel digital tools, applications, and platforms while spearheading AI/ML projects for predictive analytics and business intelligence augmentation. To excel in this role, you should hold a Bachelor's/Master's degree in Data Science, Business Analytics, Engineering, or a related field along with 8-10+ years of proven experience in automation, digital transformation, AI/ML, or data analytics. Proficiency in automation tools such as Power BI, Power Automate, Power app, Web application, and SQL is indispensable. Your expertise with AI/ML platforms like Python, TensorFlow, OpenAI, Azure AI, coupled with robust project management skills encompassing Agile, Scrum, or Six Sigma methodologies, will be highly valued. A disciplined work ethic, exceptional communication skills, and a strategic mindset geared towards automation-centric efficiency are essential traits for success in this role. At Danfoss, we are dedicated to engineering solutions that drive sustainable transformation by utilizing resources more intelligently. We strongly believe that fostering an inclusive work environment where individuals of diverse backgrounds are treated with respect and equality is paramount. Embracing the founder's mindset that actions speak louder than words, we are committed to achieving ambitious environmental targets by striving to attain CO2 neutrality by 2030.,

As a Training Program Developer specializing in Artificial Intelligence and Machine Learning, your primary responsibility will be to develop, design, and deliver comprehensive training programs on Generative AI, large language models (LLMs), Azure OpenAI, Azure AI, Machine Learning, and Deep Learning. You will be creating training materials such as presentations, hands-on labs, and documentation to support learning objectives. Conducting training sessions, workshops, and webinars for clients and internal teams to ensure a deep understanding of AI and ML concepts and their applications is a crucial part of your role. Your role will also involve staying updated with the latest advancements in AI, ML, and Generative AI technologies to continuously enhance and customize the training curriculum. Additionally, you will provide expert guidance and support to clients and internal teams on AI and ML projects, including best practices, implementation strategies, and troubleshooting. Collaboration with consulting teams to align training content with the latest features and updates in Azure AI and related technologies is essential. In this position, you will be responsible for assessing the effectiveness of training programs through feedback and evaluation, making necessary improvements to ensure high-quality learning experiences. Moreover, mentoring and coaching junior trainers and team members to build a strong and knowledgeable training team will be part of your role. To qualify for this role, you should possess a Bachelor's or Masters degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. A minimum of 5 years of experience in AI, machine learning, and deep learning, focusing on Azure AI, Azure OpenAI, and related technologies is required. Strong expertise in Open-Source large language models (LLMs), Generative AI, and applied Generative AI technologies is essential. Proficiency in using Azure services and tools like Azure Machine Learning, Azure AI Services, and Azure OpenAI is crucial. Hands-on experience with Python/C#, APIs, Notebooks, popular IDEs, and Frameworks like TensorFlow/PyTorch is necessary for this role. Excellent presentation and communication skills, along with the ability to explain complex concepts clearly and concisely, are vital. Experience in designing and delivering technical training programs, both in-person and virtual, is also required. Strong problem-solving skills and the ability to provide practical solutions to technical challenges are expected. A passion for teaching and sharing knowledge, coupled with a commitment to continuous learning and professional development, is highly valued. Preferred qualifications for this role include knowledge of multiple Hyper-scalers like Azure, AWS, or GCP, certifications in Azure AI, Azure Machine Learning, or related areas, experience in developing AI and ML applications using Python, TensorFlow, PyTorch, or similar frameworks, knowledge of AI ethics, responsible AI practices, and regulatory considerations in AI deployment, as well as familiarity with DevOps practices and tools for AI and ML projects. In addition to the technical qualifications, key personal attributes that will contribute to your success in this role include strategic and process-oriented thinking, great communication and interpersonal skills, a relentless learner with a passion for new technologies, self-motivation with eagerness to bring in new ideas for training and development, and an attitude of taking proprietorship of tasks.,

About the team Are you passionate about shaping the future of AI Join us-Responsible AIgroup inAzure AI Platform. We ensure Microsoft ships AI systems that are safe, secure, and trustworthy-empowering every person and organization on the planet to achieve more. Our team sits at the intersection of cutting-edge AI research and planet-scale production systems, powering technologies like GitHub Copilot and Azure OpenAI. You'll buildAzure AI Content Safety and RAI service integrated intoAI Studio, Azure OpenAI, AML, Cognitive Services, etc. Our mission is to empower developers and data scientists around the world and of all skill levels to easily add responsible AI capabilities to their applications. In this panel, you will have the opportunity to learn how we can protect our world, keep AI from harming everyone's lives, and apply the most advanced technologies to achieve our mission.You willfocus on identifying , measuring, mitigating, and monitoring Responsible AI risks in AI-generated and human-generated content spanning text, image, audio, video, and multimodal content, as well asdetectingabusivecustomersto prevent them frommisusing Microsoft AI products. We are looking for talents who are passionate about building customer-facing AI services with excellent customer experience, scalable and sustainable architecture, implementation and with high performance, low latency, and high availability. Microsoft's mission is to empower every person and every organization on the planet to achieve more, and we're dedicated to this mission across every aspect of our company. Our culture is centered on embracing a growth mindset and encouraging teams and leaders to bring their best each day. Join us and help shape the future of the world.

About the Role We are looking for a skilled AI/ML Engineer to help design and implement GenAI-based systems that interface with real-time enterprise data. You will be responsible for developing, fine-tuning, orchestrating, and integrating LLM-powered capabilities such as retrieval-augmented generation (RAG), function/tool calling, and data-grounded Q&A, within the Azure OpenAI ecosystem . The ideal candidate brings hands-on experience with LLM orchestration frameworks , prompt engineering, embedding models, and integrating AI systems into production-grade Azure-based platforms. Core Responsibilities LLM System Development Design and implement LLM-based pipelines , including: Prompt engineering Few-shot and zero-shot techniques Function/tool calling Chain-of-thought and structured output generation Work with Azure OpenAI , GPT-4 , and embedding models for various use cases Build conversational flows, decision trees, and fallback logic for copilots or assistants Retrieval-Augmented Generation (RAG) Develop and optimize RAG pipelines : Create embedding pipelines (e.g., using text-embedding-ada-002, Cohere, or Sentence Transformers) Chunk and index content from structured and unstructured sources (PDFs, Office files, HTML, etc.) Store and retrieve embeddings using Azure AI Search , FAISS , or Weaviate Evaluate grounding accuracy and relevance scoring Machine Learning Models Build, train, and fine-tune time series forecasting models (e.g., XGBoost, Prophet, ARIMA, or LSTM) for financial KPIs where GenAI requires predictive context Combine structured model outputs with LLM reasoning (e.g., forecasts + narrative insights) Tool/Function Integration Integrate structured data APIs, SQL endpoints, Power BI connectors, and OLAP cube access as tools/functions callable by the LLM Design input/output schemas for safe and deterministic API usage by the model Support plugin-style orchestration (LangChain/Function Calling/Semantic Kernel) Evaluation & Iteration Define custom evaluation frameworks using metrics like: Hallucination rate Grounding precision/recall Prompt latency and token efficiency Set up experiment tracking using tools like MLflow , Weights & Biases , or PromptLayer Maintain few-shot/test prompt sets and continuously refine Required Skills and Experience 36+ years of experience in AI/ML/NLP engineering Deep familiarity with LLM systems : prompt tuning, orchestration, and fine-tuning Hands-on experience with: Azure OpenAI Service LangChain , Semantic Kernel , or similar orchestration tools Vector databases (Azure AI Search, FAISS, Pinecone) Embedding model APIs (OpenAI, HuggingFace, Cohere, etc.) Strong understanding of time series modeling and ML forecasting techniques in financial domains (e.g., cost, margin, working capital, price volatility) Strong proficiency in Python , with experience in developing modular, testable code for AI/ML pipelines, API integrations, and backend services Experience building and deploying backend components (e.g. FastAPI, Flask) to serve AI models or integrate with retrieval pipelines Familiarity with best practices for production-grade AI applications , including logging, monitoring, and containerisation (e.g. Docker) Ability to work across the full stack of an AI system – from model development to integration and inference APIs Experience in building chatbots or copilots in enterprise settings Knowledge of Azure cloud services , esp. Functions , App Services , Blob Storage , and Key Vault Familiarity with enterprise systems like Power BI , SAP , or OLAP cubes

3+ years of hand-on experience with Python server-side scripting and API development. 3+ experience with Python Frameworks like Flask, Django or Fast API 2+ year of experience with Azure cloud development. Good hands-on experience with widely sued Azure services. 2+ Years of Angular/React web-UI development experience. 2+ years of hands-on experience with JavaScript, HTML, and CSS Good to Have Knowledge of Generative AI Role & responsibilities Flask and Django Frameworks Azure Functions ,Web apps and Blob storage Hands on experience with Azure AI Search Must have solid experience in building and consuming Web APIs Note : Candidate must have very good communication skills and Azure experience is mandatory Python server, API development, Cloud ( Azure AI services, Azure Web apps, Azure function apps)are mandatory Good to have - Angular or react, javascript, HTML, CSS

As a Machine Learning Engineer at Ergobite, you will be responsible for developing and deploying machine learning models using TensorFlow and/or PyTorch to create efficient and scalable solutions. Your role will involve implementing machine learning models and preprocessing tasks with Scikit-learn to optimize performance across various applications. You will have the opportunity to apply supervised and unsupervised learning algorithms like SVM and Decision Trees and design deep learning architectures such as CNNs and RNNs to address complex challenges effectively. In this role, you will conduct research and experiments with reinforcement learning techniques to enhance our capabilities. Additionally, you will contribute to the design and development of AI systems by leveraging large language models (LLMs) and advanced AI techniques. To qualify for this position, you should hold a Bachelor's or Master's degree in Engineering, Computer Science, or a related field. You must have a minimum of 3 years of Python programming experience and hands-on expertise with TensorFlow or PyTorch. Proficiency in Scikit-learn and deep learning methodologies is essential, along with experience in tools like Keras, Pandas, Numpy, and Large Language Models (LLMs) such as GPT for natural language processing and generation. Knowledge of data preprocessing techniques, feature engineering, and model evaluation metrics will be crucial for success in this role. Familiarity with version control systems, particularly Git, will also be advantageous. Preferred skills for this position include exposure to cloud-based AI development platforms like Google Cloud AI, AWS AI, or Azure AI. Knowledge of optimization techniques to enhance AI model performance and understanding of deep learning architectures like CNNs, RNNs, and transformers would be beneficial. Join us at Ergobite to be part of a dynamic team where you can apply your expertise in machine learning to drive innovation and solve real-world challenges.,

About TaskUs: TaskUs is a provider of outsourced digital services and next-generation customer experience to fast-growing technology companies, helping its clients represent, protect and grow their brands. Leveraging a cloud-based infrastructure, TaskUs serves clients in the fastest-growing sectors, including social media, e-commerce, gaming, streaming media, food delivery, ride-sharing, HiTech, FinTech, and HealthTech. The People First culture at TaskUs has enabled the company to expand its workforce to approximately 45,000 employees globally.Presently, we have a presence in twenty-three locations across twelve countries, which include the Philippines, India, and the United States. It started with one ridiculously good idea to create a different breed of Business Processing Outsourcing (BPO)! We at TaskUs understand that achieving growth for our partners requires a culture of constant motion, exploring new technologies, being ready to handle any challenge at a moment's notice, and mastering consistency in an ever-changing world. What We Offer: At TaskUs, we prioritize our employees well-being by offering competitive industry salaries and comprehensive benefits packages. Our commitment to a People First culture is reflected in the various departments we have established, including Total Rewards, Wellness, HR, and Diversity. We take pride in our inclusive environment and positive impact on the community. Moreover, we actively encourage internal mobility and professional growth at all stages of an employee's career within TaskUs. Join our team today and experience firsthand our dedication to supporting People First. Key Responsibilities 1. Strategic Transformation Leadership .Define and lead enterprise transformation programs focused on cost reduction, process efficiency, and quality improvement across global BPO operations. .Align transformation initiatives with strategic business objectives , driving outcomes around productivity, billable utilization, SLA adherence, and CX metrics (CSAT, FCR, etc.). 2. AI/ML-Driven Innovation .Identify and lead use cases for machine learning, generative AI, NLP, predictive analytics, and automation across key functions (quality assurance, workforce management, fraud detection, content moderation, etc.). .Partner with internal data science, product, and engineering teams to develop AI/ML solutions , PoCs, and production-grade deployments. 3. Process Reengineering & Six Sigma .Apply Lean Six Sigma (Black Belt certified) methodologies to redesign workflows, eliminate waste, and reduce variation in critical processes. .Conduct value stream mapping , RCA workshops, and process simulations to uncover optimization opportunities. .Develop and track transformation KPIs like AHT, TAT, Idle Time, Utilization, Attrition, and Forecast Accuracy. 4. Cross-functional Program Execution .Collaborate with business leaders, operations heads, and IT stakeholders to roll out initiatives with measurable ROI . .Manage complex transformation roadmaps with agile governance , stakeholder alignment, change management, and risk mitigation. 5. Capability Building & Change Management .Drive organizational maturity in digital transformation, citizen development, and AI literacy . .Lead CoE (Center of Excellence) for AI-augmented operations and continuous improvement . ? Required Qualifications . Bachelor's degree in Engineering, Computer Science, or a related field (Master's preferred). . Six Sigma Black Belt certification (mandatory). .12+ years of experience in BPO / KPO / Shared Services , with proven ownership of large-scale transformation projects . .5+ years of experience leading AI/ML initiatives , with demonstrable understanding of model lifecycle, deployment, and AI governance. .Proficient in tools like Python, SQL, Power BI/Tableau , and exposure to AI platforms (Azure AI, AWS SageMaker, Google Vertex AI, or OpenAI APIs). .Strong command over automation technologies (RPA tools like UiPath, Blue Prism, or Power Automate). .Deep understanding of BPO metrics and operational challenges in domains like CX, F&A, Risk, and Content Operations . ? Preferred Traits .Strategic thinker with a bias for action and problem-solving mindset . .Strong leadership presence with ability to influence C-level stakeholders. .Excellent communication and storytelling skills, especially in presenting data-backed Recommendations . .Comfortable operating in fast-paced, ambiguous, and matrixed environments . How We Partner To Protect You: TaskUs will neither solicit money from you during your application process nor require any form of payment in order to proceed with your application. Kindly ensure that you are always in communication with only authorized recruiters of TaskUs. DEI: In TaskUs we believe that innovation and higher performance are brought by people from all walks of life. We welcome applicants of different backgrounds, demographics, and circumstances. Inclusive and equitable practices are our responsibility as a business. TaskUs is committed to providing equal access to We invite you to explore all TaskUs career opportunities and apply through the provided URL .

Tech Lead GenAI & Insurance Hybrid Experience: 10+ years Reports To: Head of AI Delivery Contact : 9045052074 Role Overview: We are seeking a Tech Lead with deep expertise in architecture, system design, and Generative AI to lead high-impact projects across strategic insurance clients. The ideal candidate will combine technical depth with business acumen to translate client problems into scalable AI-driven solutions. Experience in the insurance domain is highly preferred. Key Responsibilities: Lead the architecture and technical solutioning for GenAI-powered use cases in the insurance industry. Work closely with business teams to ideate, assess, and create use cases that demonstrate tangible value. Design end-to-end systems that incorporate GenAI components, APIs, and cloud infrastructure. Own and drive technical delivery , ensuring scalability, performance, and alignment with client goals. Collaborate with engineers, product managers, and QA to deliver production-grade solutions. Serve as the technical face to the client, supporting solution discussions and managing stakeholder expectations. Evaluate and select the right set of GenAI tools and platforms (e.g., OpenAI, LangChain, RAG pipelines, etc.). Ensure data privacy, compliance, and security standards are upheld in every solution. Required Skills & Experience: 10+ years in software development/architecture with a strong track record in system design and enterprise delivery . Proven experience in designing AI/ML or GenAI solutions , preferably using tools like OpenAI, Azure OpenAI, LangChain, etc. Strong understanding of cloud infrastructure (AWS/Azure/GCP) and integration best practices. Experience working with insurance workflows like underwriting, claims, policy administration, or financial operations. Ability to create clear technical documentation , architecture diagrams, and engineering playbooks. Hands-on development experience in Python, Node.js, or similar languages is a plus. Strong stakeholder management and communication skills. Preferred Qualifications: Exposure to GenAI use cases in insurance (e.g., submission intake, risk summarization, broker email parsing, etc.) Experience working in Agile teams and fast-paced innovation environments. Familiarity with vector databases , retrieval-augmented generation (RAG), and MLOps pipelines. Prior experience leading cross-functional engineering teams.

As an AI Engineer at Microsoft CoPilot, you will play a crucial role in leveraging your expertise in AI technologies and the Microsoft ecosystem to design, build, and deploy intelligent agents and automation solutions. Your primary responsibilities will include developing AI agents using Microsoft CoPilot and related technologies, deploying AI solutions within client environments, and designing machine learning algorithms with a focus on natural language processing and conversational AI. Your role will involve collaborating with cross-functional teams to create innovative solutions using Microsoft tools and platforms. You will also be responsible for providing technical guidance and support to ensure the successful adoption and use of AI-driven tools. Additionally, staying updated on advancements in AI, machine learning, and Microsoft's AI technologies will be essential for continuous improvement. To excel in this role, you should have a strong knowledge of Microsoft Power Automate, Azure AI, and CoPilot features. Proficiency in Python and its AI/ML libraries such as TensorFlow, PyTorch, and scikit-learn is required. Familiarity with cloud-based solutions, conversational AI technologies, and chatbot frameworks will also be advantageous. A Bachelor's or Master's degree in Computer Science, Data Science, or a related field, along with proven experience in developing and deploying AI/ML models in real-world applications, is necessary. Strong programming skills, especially in Python, and familiarity with version control systems like Git are essential. Excellent problem-solving and communication skills, along with the ability to work both independently and collaboratively in a fast-paced, dynamic environment, are crucial for success in this role. If you are passionate about AI technologies and possess the required skills and expertise, we invite you to join our team as an AI Engineer at Microsoft CoPilot.,

Data Science Engineer, AS Position Overview Job Title- Data Science Engineer, AS Location- Bangalore, India Role Description We are seeking a Data Science Engineer to contribute to the development of intelligent, autonomous AI systems The ideal candidate will have a strong background in agentic AI, LLMs, SLMs, vector DB, and knowledge graphs. This role involves deploying AI solutions that leverage Retrieval-Augmented Generation (RAG) Multi-agent frameworks Hybrid search techniques to enhance enterprise applications. What we'll offer you As part of our flexible scheme, here are just some of the benefits that you'll enjoy Best in class leave policy Gender neutral parental leaves 100% reimbursement under childcare assistance benefit (gender neutral) Sponsorship for Industry relevant certifications and education Employee Assistance Program for you and your family members Comprehensive Hospitalization Insurance for you and your dependents Accident and Term life Insurance Complementary Health screening for 35 yrs. and above Your key responsibilities Design & Develop Agentic AI Applications:Utilise frameworks like LangChain, CrewAI, and AutoGen to build autonomous agents capable of complex task execution. Implement RAG Pipelines: Integrate LLMs with vector databases (e.g., Milvus, FAISS) and knowledge graphs (e.g., Neo4j) to create dynamic, context-aware retrieval systems. Fine-Tune Language Models:Customise LLMs (e.g., Gemini, chatgpt, Llama) and SLMs (e.g., Spacy, NLTK) using domain-specific data to improve performance and relevance in specialised applications. NER Models: Train OCR and NLP leveraged models to parse domain-specific details from documents (e.g., DocAI, Azure AI DIS, AWS IDP) Develop Knowledge Graphs: Construct and manage knowledge graphs to represent and query complex relationships within data, enhancing AI interpretability and reasoning. Collaborate Cross-Functionally:Work with data engineers, ML researchers, and product teams to align AI solutions with business objectives and technical requirements. Optimise AI Workflows:Employ MLOps practices to ensure scalable, maintainable, and efficient AI model deployment and monitoring. Your skills and experience 4+ years of professional experience in AI/ML development, with a focus on agentic AI systems. Proficient in Python, Python API frameworks, SQL and familiar with AI/ML frameworks such as TensorFlow or PyTorch. Experience in deploying AI models on cloud platforms (e.g., GCP, AWS). Experience with LLMs (e.g., GPT-4), SLMs (Spacy), and prompt engineering. Understanding of semantic technologies, ontologies, and RDF/SPARQL. Familiarity with MLOps tools and practices for continuous integration and deployment. Skilled in building and querying knowledge graphs using tools like Neo4j. Hands-on experience with vector databases and embedding techniques. Experience in developing AI solutions for specific industries such as healthcare, finance, or e-commerce. How we'll support you Training and development to help you excel in your career Coaching and support from experts in your team A culture of continuous learning to aid progression A range of flexible benefits that you can tailor to suit your needs About us and our teams Please visit our company website for further information: We strive for a in which we are empowered to excel together every day. This includes acting responsibly, thinking commercially, taking initiative and working collaboratively. Together we share and celebrate the successes of our people. Together we are Deutsche Bank Group. We welcome applications from all people and promote a positive, fair and inclusive work environment.