525 Generative Ai Jobs - Page 10

Role & responsibilities We are seeking a skilled Data Engineer with advanced expertise in Python, PySpark, Databricks, and Machine Learning, along with a working knowledge of Generative and Agentic AI. This role is critical in ensuring data integrity and driving innovation across enterprise systems. You will design and implement ML-driven solutions to enhance Data Governance & Data Privacy initiatives through automation, self-service capabilities, and scalable, AI-enabled innovation. Key Responsibilities: Implement ML and Generative/Agentic AI solutions to optimize Data Governance processes. Design, develop, and maintain scalable data pipelines using Python, PySpark, and Databricks. Develop automation frameworks to support data quality, lineage, classification, and access control. Develop and deploy machine learning models to uncover data patterns, detect anomalies, and enhance data governance and privacy compliance Collaborate with data stewards, analysts, and governance teams to build self-service data capabilities. Work with Databricks, Azure Data Lake, AWS, and other cloud-based data platforms for data engineering. Build, configure, and integrate APIs for seamless system interoperability. Ensure data integrity, consistency, and compliance across systems and workflows. Integrate AI models to support data discovery, metadata enrichment, and intelligent recommendations. Optimize data architecture to support analytics, reporting, and governance use cases. Monitor and improve the performance of ML/AI components in production environments. Stay updated with emerging AI and data engineering technologies to drive continuous innovation. Technical Skills: Strong programming skills in Python, PySpark, SQL for data processing and automation. Experience with Databricks and Snowflake (preferred) for building and maintaining data pipelines. Experience with Machine Learning model development and Generative/Agentic AI frameworks (e.g. LLMs, Transformers, LangChain) especially in the Data Management space Experience working with REST APIs & JSON for service integration Experience working with cloud-based platforms such as Azure, AWS, or GCP Power BI dashboard development experience is a plus. Soft Skills: Strong problem-solving skills and attention to detail. Excellent communication and collaboration abilities, with experience working across technical and business teams

Location: Any / Remote / Work From Home Employment Type: Full-time Job Summary: We are seeking skilled and innovative AI Engineers with a minimum 2-4 years of experience in developing and deploying AI solutions . The ideal candidate should have practical knowledge in AWS , Amazon Bedrock , LLMs , Claude AI , and Custom AI Development . You will contribute to the design and implementation of cutting-edge Generative AI (GenAI) and Mainstream AI applications across diverse business domains. This is an excellent opportunity to work with emerging technologies in an agile, fast-paced environment with full ownership of AI engineering pipelines. Key Responsibilities: Develop custom machine learning models and fine-tune foundation models for enterprise use Design and implement LLM-based and Generative AI solutions tailored to client use cases Work with OpenAI, Anthropic, HuggingFace models and their APIs to build secure, scalable AI systems Perform prompt engineering and experiment with parameter tuning and context optimization Build APIs and backend services to integrate AI models into product workflows Collaborate with product, data, and DevOps teams to deliver end-to-end AI-powered solutions Ensure best practices for AI model governance, security, performance, and ethical use Stay current with advancements in LLMs, vector databases (e.g., Pinecone, FAISS), and GenAI tooling Document architecture, experiments, and processes clearly and effectively Participate in peer reviews, client meetings, and cross-functional planning discussions Required Qualifications: Minimum 2-4 years of professional experience in AI/ML , with specific focus on LLMs and GenAI Strong experience working on AWS Bedrock , Lambda, and related services Proficiency in Python , including experience with libraries like HuggingFace, LangChain, etc. Familiarity with Anthropic , OpenAI , or other foundation models in production settings Experience with custom AI model development and model fine-tuning Good understanding of cloud-native AI deployments and API integrations Ability to apply prompt engineering techniques to optimize LLM responses Exposure to vector databases and RAG pipelines Strong problem-solving, communication, and team collaboration skills Preferred Qualifications (STRONG PLUS): Hands-on experience with LangChain, RAG pipelines, or agent frameworks Familiarity with AWS Sagemaker, DynamoDB, Lambda, or other AI tooling in AWS Knowledge of Docker or Kubernetes for containerizing AI workloads Understanding of MLOps principles and tools (MLflow, SageMaker Pipelines, etc.) Contributions to open-source AI projects or published GenAI applications AI/ML certifications Familiarity with enterprise use cases in biotech, healthcare, or manufacturing What We Offer: Remote work option Competitive salary package Exciting projects in the field of LLMs, AI, and cloud-native development Continuous learning opportunities in Generative AI and cloud AI tools A collaborative and fast-paced environment with a forward-thinking team Access to state-of-the-art tools and flexible project ownership How to Apply: Please submit your resume and cover letter outlining your relevant experience and why you'd be a great fit for Arocom. We differentiate candidates based on professionalism. We admire the new age methods like a video resume. If you have one please share the URL along with your resume. Your privacy is important to us, so we will not be contacting candidates by phone. If your application is selected, we will email you a link to schedule your interview at your convenient time. Please check your emails regularly, including your SPAM folder. Arocom encourages work from home and has a Bring Your Own Device (BYOD) policy. Employees / Consultants working from home are expected to use their personal laptops/desktops for work-related tasks.

The Company India's marquee global technology & consulting company. They are an international flag-bearer of technical and managerial excellence. With offices around the globe, the company has a comprehensive presence across multiple segments of the technology product and service industries as well as a blue-chip roster of clients for their Consulting engagements. They are a respected career company and a long-term wealth creator. The Job We are seeking an experienced 3+ years of IT experience ( 2 Years in AI/ML/DS Domain). Gen AI Development : Data collection and preparation: Collect and prepare data for training and evaluating LLMs. This may involve cleaning and processing text data, or creating synthetic data. Model development: Design and implement LLM models. This may involve choosing the right architecture, training the model, and tuning the hyperparameters. Model evaluation: Evaluate the performance of LLM models. This may involve measuring the accuracy of the model on a held-out dataset, or assessing the quality of the generated text. Model deployment: Deploy LLM models to production. This may involve packaging the model, creating a REST API, and deploying the model to a cloud computing platform. Responsible AI: Should have proficient knowledge in Responsible AI and Data Privacy principles to ensure ethical data handling, transparency, and accountability in all stages of AI development. Must demonstrate a commitment to upholding privacy standards, mitigating bias, and fostering trust within data-driven initiatives. Experience in working with ML toolkit like R, NumPy, MatLab etc.. Experience in data mining, statistical analysis and data visualization Your Profile Roles and Responsibility: LLM Development/Deployment Pipeline creation, workflows Study and transform Gen AI PoCs to production grade deployment Design machine learning systems, Run machine learning tests and experiments Research and implement appropriate ML algorithms and tools Develop machine learning applications according to requirements Select appropriate datasets and data representation methods Perform statistical analysis and fine-tuning using test results Train and retrain systems when necessary

Responsibilities The Graphic Designer role for the Large Deals Business Narrative team integrates into a complex, strategic sales environment. In this role, Graphic Designers will support assigned activities under the guidance of a Lead Designer or Writer. Primary responsibilities include creating proposal response documents and presentations, marketing collateral, brand Identity packages, customized communication in both physical and digital formats, microsites, and multimedia elements such as video and audio recordings. Additionally, Graphic Designers are expected to engage in conceptualization activities, participate in strategy discussions, and attend team-wide enablement meetings. Responsibilities: Strong graphic design fundamentals (typography, color theory, hierarchy, contrast, and grid/alignments). Ability to abide by brand guidelines and possess a strong knowledge of design standards. Assist Lead Designers in the creation of various design projects throughout the entire project lifecycle. Enhance graphic visualization concepts based on guidance from Lead Designers to produce finalized artifacts. Capable of understanding specifics required to produce various presentation and design artifacts (dimensions, DPI, file size, etc.). Manage multiple concurrent assignments with defined timelines with the assistance of workload planning from Designer and Writer team leaders Demonstrate proficiency in designing PPT decks, brand identity, campaign branding, posters, booklets, handouts, emailers, sales videos, and animated PPTs for client meetings. Must Have skills: Demonstrate the ability to understand Large Deals sales activities and create plans from brainstorming ideas to the final execution of deliverables for assigned projects. Be present in-person with a team during critical activities for assigned projects. Exhibit strong teamwork and interpersonal skills, articulating ideas clearly during meetings to help non-creative stakeholders visualize concepts. Showcase problem-solving skills by presenting multiple solutions that communicate complex information clearly. Fluency in both spoken and written English is necessary to succeed in this role. Possess sound knowledge of design tools such as Adobe Photoshop, Illustrator, InDesign, Premiere, After Effects, and MS Office tools like PowerPoint and Word. Knowledge of additional design tools like 3D Studio Max or Generative AI is a bonus. Preferred Skills: Domain->Communication Design->Graphic Design Educational Requirements Bachelor of Arts Service Line Strategic Large Deals team * Location of posting is subject to business requirements

We are seeking a highly skilled Senior Machine Learning Engineer to join our dynamic team. The ideal candidate will have a deep understanding of Machine Learning, AI, and cloud platforms like Azure. You will play a key role in designing, developing, and deploying ML models and Generative AI solutions to solve complex business problems. Role overview Engineering Masters degree or PhD in Data Science, Statistics, Mathematics, or related fields 5 years+ experience in a Machine Learning Engineer role into large corporate organizations Experience of working with ML models in a cloud ecosystem. Statistics & amp; Machine Learning Statistics : Strong understanding of statistical analysis and modelling techniques (e.g., regression analysis, hypothesis testing, time series analysis) Classical ML : Very strong knowledge in classical ML algorithms for regression & classification, supervised and unsupervised machine learning, both theoretical and practical (e.g. using scikit-learn, xgboost) ML niche : Expertise in at least one of the following ML specialisations: Timeseries forecasting / Natural Language Processing / Computer Vision Deep Learning: Good knowledge of Deep Learning fundamentals (CNN, RNN, transformer architecture, attention mechanism, ) and one of the deep learning frameworks (pytorch, tensorflow, keras) Generative A I: Good understanding of Generative AI specificities and previous experience in working with Large Language Models is a plus (e.g. with openai, langchain). MLOps Model strategy : Expertise in designing, implementing, and testing machine learning strategies. Model integration : Very strong skills in integrating a machine learning algorithm in a data science application in production. Model performance : Deep understanding of model performance evaluation metrics and existing libraries (e.g., scikit-learn, evidently) Model deployment: Experience in deploying and managing machine learning models in production either using specific cloud platform, model serving frameworks, or containerization. Model monitoring : Experience with model performance monitoring tools is a plus (Grafana, Prometheus). Software Engineering Python: Very strong coding skills in Python including modularity, OOP, data & config manipulation frameworks (e.g., pandas, pydantic) etc. Python ecosystem : Strong knowledge of tooling in Python ecosystem such as dependency management tooling (venv, poetry), documentation frameworks (e.g. sphinx, mkdocs, jupyter-book), testing frameworks (unittest,pytest) Software engineering practices: Experience in putting in place good software engineering practices such as design patterns, testing (unit, integration), clean code, code formatting etc. Debugging: Ability to troubleshoot and debug issues within machine learning pipelines. Data Science Experimentation and Analytics Data Visualization: Knowledge of data visualization tools such as plotly, seaborn, matplotlib, etc. to visualise, interpret and communicate the results of machine learning models to stakeholders. Basic knowledge of PowerBI is a plus. Data Cleaning: Experience with data cleaning and preprocessing techniques such as feature scaling, dimensionality reduction, and outlier detection (e.g. with pandas, scikit-learn). Data Science Experiments: Understanding of experimental design and A/B testing methodologies. Data Processing: Databricks/Spark: Basic knowledge of PySpark for big data processing Databases : Basic knowledge of SQL to query data in internal systems Data Formats: Familiarity with different data storage formats such as Parquet and Delta. DevOps Azure DevOps : Experience using a DevOps platform such as Azure DevOps for using Boards, Repositories, Pipelines Git : Experience working with code versioning (git), branch strategies, and collaborative work with pull requests. Proficient with the most basic git commands. CI / CD : Experience in implementing/maintaining pipelines for continuous integration (including execution of testing strategy) and continuous deployment is preferable. Cloud Platform: Azure Cloud: Previous experience with services like Azure Machine Learning Services and/or Azure Databricks on Azure is preferable. Soft skills: Strong analytical and problem-solving skills, with attention to detail Excellent verbal and written communication and pedagogical skills with technical and non-technical teams Excellent teamwork and collaboration skills Adaptability and reactivity to new technologies, tools, and techniques Fluent in English. What would you do here: Managing the lifecycle of machine learning models Develop and implement machine learning models to solve complex business problems. Ensure that models are accurate, efficient, reliable, and scalable. Deploy machine learning models to production environments, ensuring that models are integrated with software systems. Monitor machine learning models in production, ensuring that models are performing as expected and that any errors or performance issues are identified and resolved quickly. Maintain machine learning models over time. This includes updating models as new data becomes available, retraining models to improve performance, and retiring models that are no longer effective. Develop and implement policies and procedures for ensuring the ethical and responsible use of machine learning models. This includes addressing issues related to bias, fairness, transparency, and accountability. Continuous Improvements: Stay up to date with the latest developments in the field: read research papers, attend conferences, and participate in trainings to expand their knowledge and skills. Identify and evaluate new technologies and tools that can improve the efficiency and effectiveness of machine learning projects. Propose and implement optimizations for current machine learning workflows and systems. Proactively identify areas of improvement within the pipelines. Make sure that created code is compliant with our set of engineering standards. Collaboration with other data experts (Data Engineers, Platform Engineers, and Data Analysts) Participate to pull requests reviews coming from other team members. Ask for review and comments when submitting their own work. Actively participate to the day-to-day life of the project (Agile rituals), the data science team (DS meeting) and the rest of the Global Engineering team.

We are seeking an experienced AI/ML Architect to lead the design, development, and deployment of Generative AI solutions. This role requires a deep understanding of AI/ML architectures, technical leadership, and the ability to design robust, scalable, and production-ready systems. The ideal candidate will have extensive experience in cloud platforms like GCP and optionally AWS, Azure, or equivalent tools, combined with hands-on expertise in MLOps, containerization, data processing, and advanced model optimization . You will work closely with cross-functional teams, technical leadership, and stakeholders to implement state-of-the-art AI solutions that solve real-world challenges and drive business value. Roles & Responsibilities 1) Technical Leadership Lead the technical design and architecture of complex Generative AI systems. Ensure solutions align with business objectives, scalability requirements, and technical feasibility. Guide development teams through best practices , architecture reviews, and technical decision-making processes. 2) Solution Architecture Design and develop end-to-end Generative AI solutions , including data pipelines , model training, deployment, and real-time monitoring. Utilize MLOps tools and frameworks to automate workflows, ensuring scalable and repeatable deployments. Architect robust solutions using GCP and optionally AWS, Azure, or open-source frameworks. Design, train, and fine-tune AI/ML models , especially Generative AI and Large Language Models (LLMs) , to address specific use cases. Build conversational AI solutions and chatbots using frameworks such as LangChain , RAG (Retrieval-Augmented Generation) , and Chain-of-Thought (COT) prompting . 3) Production Deployment Lead the deployment of Generative AI models into production environments . Optimize deployment pipelines leveraging tools like Docker, Kubernetes , and cloud-native services for orchestration. Ensure seamless integration of GenAI solutions into existing CI/CD pipelines. 4) Data Processing & Feature Engineering Build scalable ETL workflows for managing structured, semi-structured, and unstructured data. Implement data wrangling , preprocessing, and feature engineering pipelines to prepare data for Generative AI applications. Optimize workflows to extract meaningful insights from large datasets . 5) Model Optimization Identify and implement optimization strategies such as hyperparameter tuning , feature engineering , and model selection for performance enhancement. Focus on computational efficiency and scaling models to production-level performance. 6) Pilot/POCs Development Drive the design and development of Proof of Concepts (POCs) and pilot projects to address customer requirements. Collaborate with delivery and product teams to scale successful pilots to production-grade solutions. 7) Evangelization Promote and drive the adoption of Generative AI solutions across customer and delivery teams. Provide technical leadership and mentorship to teams working on GenAI projects. Conduct workshops, training sessions, and knowledge-sharing initiatives to enable stakeholders. 8) Continuous Improvement Stay at the forefront of AI advancements , frameworks, and tools, including emerging concepts in Generative AI. Explore and evaluate techniques like Reinforcement Learning from Human Feedback (RLHF) and REACT (Retrieve, Extract, Adapt, Construct, Think) frameworks to enhance GenAI applications. Required Skills & Qualifications 10+ years of experience in AI/ML architecture, model development, and production deployment Proven expertise in designing, implementing, and scaling Generative AI and LLM-based solutions Hands-on experience with frameworks like LangChain , Retrieval-Augmented Generation (RAG) , and advanced prompting techniques Proficiency in advanced techniques such as embeddings and Chain-of-Thought (COT) prompting Experience working with cloud platforms , primarily GCP , with optional experience in AWS or Azure Strong understanding of MLOps tools, pipelines, and model monitoring in production Proficiency in Python and SQL for model development and data processing Experience with data preprocessing, ETL workflows , and feature engineering for AI applications Strong knowledge of containerization tools like Docker and orchestration platforms like Kubernetes Solid understanding of CI/CD pipelines for continuous deployment and integration of AI solutions Experience working with large datasets for structured and unstructured AI applications Deep experience in model optimization, including hyperparameter tuning and computational efficiency strategies Proven track record of leading POCs/pilots and scaling them to production-grade deployments Preferred Skills Familiarity with Reinforcement Learning from Human Feedback (RLHF) . Experience with REACT (Retrieve, Extract, Adapt, Construct, Think) frameworks. Strong understanding of orchestration for large-scale production environments. Key Attributes Strong technical leadership and mentorship abilities. Excellent communication and stakeholder management skills. Strategic thinking with the ability to architect scalable and future-ready AI systems. Passion for solving business challenges using state-of-the-art AI techniques. Commitment to staying updated with the latest advancements in AI/ML technologies. Why Join Us? Lead the development of cutting-edge Generative AI solutions for real-world applications. Be part of a collaborative, innovative, and technology-driven team. Opportunity to work with advanced AI/ML tools and frameworks. Drive innovation through technical leadership , mentorship, and solution evangelization. Continuous professional growth with access to the latest AI/ML technologies and frameworks.

Role Purpose The purpose of this role is to develop minimum viable product (MVP) and comprehensive AI solutions that meet and exceed clients expectations and add value to business. Do Manage the product/ solution development using the desired AI techniques Lead development and implementation of custom solutions through thoughtful use of modern AI technology Review and evaluate the use cases and decide whether a product can be developed to add business value Create the overall product development strategy and integrating with the larger interfaces Create AI models and framework and implement them to cater to a business problem Draft the desired user Interface and create AI models as per business problem Analyze technology environment and client requirements to define product solutions using AI framework/ architecture Implement the necessary security features as per products requirements Review the used case and see the latest AI that can be used in products development Identify problem areas and perform root cause analysis and provide relevant solutions to the problem Tracks industry and application trends and relates these to planning current and future AI needs Create and delegate work plans to the programming team for product development Interact with Holmes advisory board for knowledge sharing and best practices Responsible for developing and maintaining client relationships with the key strategic partners and decision makers Drive discussions and provide consultation around product design as per customer needs Participate in client interactions and gather insights regarding product development Interact with vertical delivery and business teams and provide and correct responses to RFP/ client requirements Assist in products demonstration and receive feedback from the client Design presentations for seminars, meetings and enclave primarily focused over product Team Management Resourcing Forecast talent requirements as per the current and future business needs Hire adequate and right resources for the team Talent Management Ensure adequate onboarding and training for the team members to enhance capability & effectiveness Build an internal talent pool and ensure their career progression within the organization Manage team attrition Drive diversity in leadership positions Performance Management Set goals for the team, conduct timely performance reviews and provide constructive feedback to own direct reports Ensure that the Performance Nxt is followed for the entire team Employee Satisfaction and Engagement Lead and drive engagement initiatives for the team Track team satisfaction scores and identify initiatives to build engagement within the team Deliver No.Performance ParameterMeasure 1. Continuous technical project management & deliveryAdoption of new technologies, IP creation, MVP creation, Number of patents filed, Research papers created 2. Client CentricityNo. of automation done, On-Time Delivery, cost of delivery, optimal resource allocation 3. Capability Building & Team Management% trained on new age skills, Team attrition %, Number of webinars conducted (internal/external) Mandatory Skills: Generative AI.

The Role Machine learning and data science are interdisciplinary fields that require a combination of skills in mathematics, statistics, programming, and domain-specific knowledge to extract meaningful insights from data and develop predictive models. Skills Requirements Mandatory Skillset - ML Techniques, any ML Framework, Gen AI COncepts, Azure, Python Secondary Skillset - AWS, or Google Cloud Requirements Work closely with cross-functional teams to understand business requirements and translate them into machine learning solutions. Collect, clean, and pre-process large datasets to prepare them for machine learning models. Develop and implement machine learning algorithms and models for solving specific business problems. Collaborate with data engineers to ensure seamless integration of machine learning models into production systems. Fine-tune models for optimal performance and conduct thorough testing and validation. Stay updated on the latest advancements in machine learning and artificial intelligence and assess their potential impact on our projects. Effectively communicate complex technical concepts and findings to non-technical stakeholders. Monitor and maintain deployed models and update them as needed to adapt to changes in data or business requirements. Adhere to ethical standards and ensure that machine learning solutions comply with relevant regulations. Proficiency in Python with hands-on experience in cloud platforms including GCP, AWS, and Azure; strong skills in API integration.

Job description Looking for SDET/ Automation testing with Gen AI Testing Interested ones share CV and below details to snidafazli@altimetrik.com Name(as per aadhar card): Phone Number: EmailID: Current CTC: Fixed CTC: Expected CTC: holding any offers: Current Company: Payroll Company: Notice period: If serving Notice period, exact LWD: Current Location: Preferred location: Total years of experience: Relevant Experience below in years, SDET: Gen AI Testing: JAva: Selenium: API Automation: Rest Assured: BDD: Cucumber:

Senior AI & ML Platform Engineer Location: Bengaluru Experience Level: 3 to 10 Years About the Role We are building next-generation AI-powered platforms that leverage Large Language Models (LLMs), advanced Machine Learning (ML), NLP, and agentic workflows to automate critical business processes across multiple domains. We are looking for experienced AI/ML Engineers who are passionate about building real-world AI productsnot just experimenting. You will help design, prototype, and deploy intelligent systems integrating LLMs, agents, APIs, and robust ML models for classification, prediction, and optimization. Responsibilities Build and integrate agentic AI workflows using LangChain or similar frameworks. Develop APIs and backend services to support LLM and ML-driven platforms. Implement, train, and optimize lightweight and scalable ML models for classification, prediction, and anomaly detection. Work with LLMs (OpenAI, Claude, Gemini) to fine-tune prompts, create retrieval-augmented generation (RAG) systems, and chain multi-step tasks. Design and optimize vector search implementations for LLM-driven applications. Integrate AI models with external systems (VMS platforms, ERP systems) using APIs. Implement document processing pipelines combining OCR with LLM/ML validation. Apply ML techniques for supply-demand forecasting, fraud detection, and optimization. Participate in design discussions, brainstorming sessions, and agile sprints. Collaborate with senior AI architects and SMEs to refine platform capabilities. Required Skills Strong experience in Python for ML and AI development. Expertise in ML frameworks such as TensorFlow, PyTorch, scikit-learn. Knowledge of NLP tasks (text extraction, classification, summarization). Experience building and optimizing RAG workflows with vector databases. Solid understanding of API development (FastAPI, Flask, or similar frameworks). Familiarity with prompt engineering and agent orchestration concepts. Ability to build scalable ML models for classification, forecasting, and anomaly detection. Experience integrating ML solutions with cloud services (AWS, Azure, GCP). Knowledge of OCR tools and techniques for document processing. Exposure to multi-agent architectures and reinforcement learning is a plus. Understanding of feature engineering, model evaluation, and optimization techniques. Mindset We Are Looking For Builders mindset: You love turning ideas into working solutions fast. Curiosity: Passionate about keeping up with the latest in GenAI and ML. Problem-solver: Comfortable working in ambiguous environments where solutions need discovery, not just execution. Collaboration: Open to learning from senior architects and iterating based on feedback.

Job Title: AI Technical Lead Location: Bengaluru, work from Avaali office Employment Type: Full-time Reports to: CTO Key Responsibilities 1. Develop and Execute AI Initiatives Collaborate closely with business stakeholders at all levels to identify and implement AI-driven solutions that address key pain points and deliver measurable outcomes. Actively participate in multidisciplinary and cross-functional (fusion) teams to support the entire lifecycle of AI projectsfrom ideation to execution. Stay on top of cutting-edge AI trends, innovations, and best practices in the industry while leveraging these insights to deliver impactful solutions. 2. Design and Implement AI Solutions Architect AI-based solutions that align with Avaali's vision of operational cost optimization and margin improvement for clients. Ensure that all AI solutions are scalable, secure, governed, and adhere to applicable regulations and compliance standards. Create personalized solutions aligned with specific business requirements and ensure the delivery of high-quality outcomes. 3. Build and Scale the AI Practice in collaboration with the CTO Develop and implement standardized methodologies, frameworks, and best practices to drive consistency and excellence across AI initiatives. Create knowledge-sharing forums, training modules, and certifications to upskill internal teams and establish Avaali as a center of excellence for AI. This person would support the CTO in this area (he/she will be an important team member in this activity) Required Skills and Competencies Deep knowledge of AI/ML technologies, frameworks, and platforms, including hands-on experience with AI-based tools and cloud ecosystems. Strong expertise in designing enterprise-class AI systems that balance innovation with security, governance, and compliance needs. Proven track record of managing large-scale AI initiatives across industries, including successful implementation of impactful solutions. Outstanding analytical and problem-solving skills combined with a strategic mindset that embraces emerging opportunities. Qualifications Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field. Advanced degrees preferred. Minimum 8 years of experience including in AI leadership roles, ideally including consultancy or enterprise environments. Demonstrated success in building and scaling AI capabilities and teams. Experience defining and managing budgets for AI initiatives while delivering cost-effective outcomes. Benefits of Joining Avaali Be a key player in driving transformational change in cutting-edge industries. Work with a highly skilled and innovative team eager to push the boundaries of what AI can achieve. Opportunity to develop AI solutions with real-world impact, empowering businesses to thrive in a digital-first era. If you are ready to shape the future of AI at scale, we invite you to apply for this role.

Role & responsibilities Architect and implement AI/ML solutions tailored to client-specific business problems using Gen AI (e.g., LLMs like GPT, Gemini, Mistral) and traditional ML models (e.g., scikit-learn, XGBoost). Collaborate with client stakeholders to understand requirements, define problem statements, and translate them into scalable AI/ML solutions. Present demos and proof-of-concepts (POCs) to clients, showcasing the value of AI/ML in real-world scenarios Mentor and guide a cross-functional team of data scientists, ML engineers, and developers Drive best practices in model development, deployment, and monitoring Stay abreast of the latest advancements in Gen AI and ML, and evaluate their applicability to client use cases Contribute to internal knowledge bases and reusable solution accelerators Preferred candidate profile Strong programming skills in Python and experience with ML libraries (e.g., TensorFlow, PyTorch, scikit-learn). Hands-on experience with Gen AI platforms and LLMs (e.g., OpenAI, Gemini, LLaMA, Mistral). Proven track record of deploying ML models in production environments (cloud/on-prem). Experience with API development, data pipelines, and dashboarding tools like Streamlit. Familiarity with DevOps and MLOps practices for model lifecycle management. Excellent communication and stakeholder management skills. Tools: LLM, SLM, Vector DB, Graph DB, Airflow, MLFlow, MLOps tools, NLP, KG, ML models (Regression, Clustering, Classification etc), LangChain, LangGraph, AutoGen

Job Description: Lead Solution Architect with experience in government programs preferred The candidate is expected to play the role of an expert level Technical Solution Architect in large programs The resource should mandatorily have minimum 10 Years experience in solution planning and system architecture designing with at least 5 years of experience as a Lead Architect for Analytical Systems The resource should have demonstrated extensive experience in the use of various techniques to develop robust data warehouse business intelligence AI solutions which have significant weightage to statistical and advanced analytics Key Responsibilities: ROLE AND RESPONSIBILITIES As a Principal Technical Solution Architect lead the engagement efforts at different stages from problem definition to diagnosis to solution design development deployment in large government implementation programs Create detailed design and architecture and process artifacts implement the solution and the deployment plan Connect with senior client business and IT stakeholders demonstrating thought leadership in domain process and technology Contribute to Unit and Organizational initiatives and COEs REQUIRED SKILLS AND EXPERIENCE Domain process functional technical Strong hands on and in depth knowledge of Data Analytics module Strong understanding of the Data Warehousing Business Intelligence AI solutions good understanding of airlines industry Thorough understanding of Agile methodologies Good understanding of business processes in the airlines domain or with government organizations Experience in leading and driving Business process workshops and Fit GAP analysis Should have working experience in a highly regulated environment Should be aware of release governance processes and have experience in working on any incident management tool Preferred Skills: Technology->Machine Learning->Generative AI,Technology->Machine Learning->AI/ML Solution Architecture and Design->traditional ai ml

7-10 years of experience in machine learning, deep learning. Experience End-to-end architecture design for machine learning solutions Deployment of AI models into scalable services Staying at the forefront of generative AI advancements Optimizing models for performance and scalability Collaborating with cross-functional teams for successful project delivery Degree in Computer Science, Information Technology, Electrical Engineering, or related field Experience or understanding of machine learning, deep learning, generative AIand MLOps Knowledge of deep learning techniques and frameworks (TensorFlow, PyTorch) Familiarity with cloud platforms, preferably Microsoft Azure A certification in AI or machine learning is advantageous Strong analytical and problem-solving skills Excellent communication and team collaboration abilities

Job Summary We are seeking highly skilled Sr. Backend Developers with an experience of 8 - 12 years to join our dynamic team. The ideal candidates should have strong expertise in Node.js , along with experience in Python, Generative AI (Gen AI) , and Natural Language Processing (NLP) preferred. Additionally, experience working with MongoDB, AWS Lambda, and cloud-based deployments is required. Key Responsibilities: Design, develop, and maintain scalable applications using Node.js and Python. Implement and optimize NLP models and Gen AI solutions for various applications. Develop and manage RESTful APIs and microservices using Node.js. Work with MongoDB for database management and optimization. Deploy and manage applications in AWS Lambda and other AWS services. Collaborate with cross-functional teams to integrate AI-driven solutions into the platform. Troubleshoot and debug applications, ensuring high availability and reliability. Required Skills & Experience: 8-12 years of hands-on experience in Backend Development using Node Js. Strong proficiency in Python, especially in AI/ML frameworks (TensorFlow, PyTorch, etc.). Experience working with Natural Language Processing (NLP) or Generative AI models. Proficiency in MongoDB, including database design and performance tuning. Hands-on experience with AWS Lambda and serverless architectures. Strong knowledge of REST APIs, GraphQL, and microservices. Experience with Docker, Kubernetes, and CI/CD pipelines is a plus. Ability to work in an Agile environment and collaborate with remote teams

What Your Responsibilities Will Be Lead and manage a team of AIML engineers, overseeing project lifecycles from conception to deployment, ensuring high-quality standards and timely delivery. Mentor and develop team members, providing guidance on technical challenges, career development, and professional growth opportunities. Stay abreast of the latest AIML technologies and methodologies, incorporating new and innovative approaches into our projects to maintain competitive advantage. Develop and execute our AIML strategy, aligning with the company's objectives, and ensuring the team's projects support this vision. Collaborate with cross-functional teams, including product management, engineering, and design, to define project requirements, set priorities, and allocate resources effectively. Ensure operational excellence, implementing best practices in project management, software development, and quality assurance to optimize team performance and productivity. Manage stakeholder communications, providing regular updates on project status, key milestones, and any challenges or risks, ensuring alignment and support across the organization. What You'll Need to be Successful Specific Qualifications Proven expertise in Gen AI technologies and methodologies, with a strong portfolio of projects demonstrating your ability to apply these in solving complex problems. Experience with building and deploying to enterprise production environments APIs powered by AI Machine Learning systems. Proficiency in programming languages relevant to AI ML, such as Python, R, Java, Scala, C++ and familiarity with AI ML frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn). Experience with cloud computing platforms (AWS, Azure, Google Cloud) and understanding of how to leverage these for scalable, secure, reliable distributed systems with complex workflows relying on AI ML solutions. Strong background in data engineering and familiarity with database technologies, as well as, data processing / ETL pipelines and visualization tools. General Qualifications Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related science field. A minimum of 10 years of experience in AI ML with at least 5 years in a leadership or management position, overseeing technical teams. Excellent project management skills, with experience in agile methodologies.

Experience working closely with other data scientists, data engineers' software engineers, data managers and business partners. 7+ years in designing, planning, prototyping, productionizing, maintaining knowledge in Python, Go, Java, SQL knowledge

Role Summary The Ecosystem Engineering Technology Engineer is responsible for guiding and supporting partners in embedding, sell-to, resell, and influence scenarios with IBM's strategic technologies. Activities include deal support with partners selling to clients and co-creating with partners (Joint Solutions, Assets, embedding of IBM technology). The Technology Engineer is part of a cross-functional team that delivers a unique co-creation experience for partners to accelerate and scale the embedding and use of IBM's strategic technologies to/in partner solutions. They use contemporary technologies and approaches to design, develop, test, and co-deliver solutions across the IBM Technology platform; They work closely with the Ecosystem Engineering: Solution Architect(s) to determine the feasibility of the solution and collaborate with the partner's and other Technology Engineers to implement a comprehensive solution. Ecosystem Technology Engineers are asked to specialize in a brand or set of capabilities to provide deep technical skills in their area of expertise. Required Education Bachelor's Degree Preferred Education Bachelor's Degree Required Technical and Professional Expertise Expert level knowledge in IBM Business Automation suite of products (CP4BA - RPA, BPM - BAW, Process Mining, FileNet) . Very good understanding of Generative AI (IBM watsonx platform or equivalent) . Hands-on coding experience in Python, Java, Node.js, JavaScript, React . Agentic AI framework will be an added advantage. Excellent communication and presentation skills.

Your role and responsibilities Back end development with GoLang Expertise in Kubernetes/OpenShift, Cloud service providers. Knowledge of Generative AI, and ability to integrate AI to applications. Ability to pick up new areas based on business requirements Excellent communication skills Required education Bachelor's Degree Required technical and professional expertise 6+ years of overall experience in backend development. Excellent understanding of system design and best practices. 6+ years of application development with GoLang development. Good level of expertise in Kubernetes or OpenShift, use of Docker/Podman and Cloud service providers. Good level of knowledge of CNI, container native storage. Expertise in Version Control - Git Experience using cloud technologies (AWS/GCP/Azure/IBM Cloud) Experience with Ansible and Shell scripting Proficient in Linux administration. Experience of IaC (Terraform) Expertise in Version Control - Git Design functional DevOps application lifecycle. Good understanding of CICD pipelines such as Jenkins. Should have hands-on in writing and debugging Jenkinsfile Experience using build tools such as Maven, Gradle, Make, Ant Knowledge of AI - Pytorch, TensorFlow, Scikit,Generative AI, and ability to integrate AI functionalities to applications. ABOUT BUSINESS UNIT IBM Systems helps IT leaders think differently about their infrastructure. IBM servers and storage are no longer inanimate - they can understand, reason, and learn so our clients can innovate while avoiding IT issues. Our systems power the world's most important industries and our clients are the architects of the future.Join us to help build our leading-edge technology portfoliodesigned for cognitive business and optimized for cloud computing.

Design, develop, & optimize AI-powered apps Implement large language models (LLMs) & generative AI apps Integrate Copilot Studio, Azure AI Search, and other AI/ML platforms into enterprise solutions RAG (Retrieval-Augmented Generation) architecture Required Candidate profile 7+ yrs of exp in Python, C#, Java, JavaScript, C++ Generative AI capabilities Strong .NET Full Stack exp 3+ yrs of experience as Full Stack Developers & AI exposure can apply not a Data Scientist role

Requirement Role: ML Engineer/Data Scientist Experience: 3 to 15 Years Job Description: Responsibilities: Strong understanding of ML algorithms, techniques, and best practices. Strong understanding of Databricks, Azure AI services and other ML platforms and cloud computing platforms (e.g., AWS, Azure, GCP) and frameworks (e.g., TensorFlow, PyTorch, scikit-learn). Strong understanding of Mlflow or Kubeflow frameworks Strong programming skills in python and Data analytical expertise Experience in building Gen AI based solutions like chatbots using RAG approaches Expertise in any of the gen ai frameworks such as Langchain/ Langgraph, autogen, crewai, etc. Requirements: Proven experience as a Machine Learning Engineer, Data Scientist, or similar role, with a focus on product matching, image matching, and LLM. Solid understanding of machine learning algorithms and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Hands-on experience with product matching algorithms and image recognition techniques. Experience with natural language processing and large language models (LLMs) such as GPT, BERT, or similar architectures. Optimize and fine-tune models for performance and scalability.. Collaborate with cross-functional teams to integrate ML solutions into products. Stay updated with the latest advancements in AI and machine learning.

Technical Lead AI & Data Warehouse (DWH) Pando is a global leader in supply chain technology, building the world's quickest time-to-value Fulfillment Cloud platform. Pandos Fulfillment Cloud provides manufacturers, retailers, and 3PLs with a single pane of glass to streamline end-to-end purchase order fulfillment and customer order fulfillment to improve service levels, reduce carbon footprint, and bring down costs. As a partner of choice for Fortune 500 enterprises globally, with a presence across APAC, the Middle East, and the US, Pando is recognized as a Technology Pioneer by the World Economic Forum (WEF), and as one of the fastest growing technology companies by Deloitte. Role As the Senior Lead for AI and Data Warehouse at Pando, you will be responsible for building and scaling the data and AI services team. You will drive the design and implementation of highly scalable, modular, and reusable data pipelines, leveraging big data technologies and low-code implementations. This is a senior leadership position where you will work closely with cross-functional teams to deliver solutions that power advanced analytics, dashboards, and AI-based insights. Key Responsibilities Lead the development of scalable, high-performance data pipelines using PySpark or Big Data ETL pipeline technologies. Drive data modeling efforts for analytics, dashboards, and knowledge graphs. Oversee the implementation of parquet-based data lakes. Work on OLAP databases, ensuring optimal data structure for reporting and querying. Architect and optimize large-scale enterprise big data implementations with a focus on modular and reusable low-code libraries. Collaborate with stakeholders to design and deliver AI and DWH solutions that align with business needs. Mentor and lead a team of engineers, building out the data and AI services organization. Required 8-10 years of experience in big data and AI technologies, with expertise in PySpark or similar Big Data ETL pipeline technologies. Strong proficiency in SQL and OLAP database technologies. Firsthand experience with data modeling for analytics, dashboards, and knowledge graphs. Proven experience with parquet-based data lake implementations. Expertise in building highly scalable, high-volume data pipelines. Experience with modular, reusable, low-code-based implementations. Involvement in large-scale enterprise big data implementations. Initiative-taker with strong motivation and the ability to lead a growing team. Preferred Experience leading a team or building out a new department. Experience with cloud-based data platforms and AI services. Familiarity with supply chain technology or fulfilment platforms is a plus.

Role: ML Engineer Experience: 3 to 15 Years Chennai location must or relocation also fine- Hybrid mode We have good budget Job Description: Responsibilities: Strong understanding of ML algorithms, techniques, and best practices. Strong understanding of Databricks, Azure AI services and other ML platforms and cloud computing platforms (e.g., AWS, Azure, GCP) and frameworks (e.g., TensorFlow, PyTorch, scikit-learn). Strong understanding of Mlflow or Kubeflow frameworks Strong programming skills in python and Data analytical expertise Experience in building Gen AI based solutions like chatbots using RAG approaches Expertise in any of the gen ai frameworks such as Langchain/ Langgraph, autogen, crewai, etc. Requirements: Proven experience as a Machine Learning Engineer, Data Scientist, or similar role, with a focus on product matching, image matching, and LLM. Solid understanding of machine learning algorithms and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Hands-on experience with product matching algorithms and image recognition techniques. Experience with natural language processing and large language models (LLMs) such as GPT, BERT, or similar architectures. Optimize and fine-tune models for performance and scalability.. Collaborate with cross-functional teams to integrate ML solutions into products. Stay updated with the latest advancements in AI and machine learning.

AI Engineer & Lead This role is a blend of technical innovation, strategic consulting, and hands-on problem-solving, making each day varied, challenging, and impactful. Exp: 3-8 Years Location: Chennai & Hyderabad Organization: Intellect Design Arena - Product Company ------------------------------------------------------------------------------------------------------------- About Intellect Design Arena Limited Intellect Design Arena Ltd is an enterprise-grade financial technology leader, providing composable and intelligent solutions for futuristic global financial institutions across 57 countries. Intellects revolutionary First Principles Thinking-based Enterprise Connected Intelligence Platform, eMACH.ai, is the most comprehensive, composable, and intelligent open finance platform in the world. With an impressive array of 329 microservices, 535 events, and over 1757 APIs, eMACH.ai enables financial institutions to design and deploy future-ready technology solutions that provide a significant global competitive edge. With three decades of domain expertise, Intellect offers a full spectrum of banking and insurance technology products through four lines of business: Global Consumer Banking (iGCB), Global Transaction Banking (iGTB), IntellectAI and Digital Technology for Commerce (iDTC). Intellect is a pioneer in applying Design Thinking and our 8012 FinTech Design Center, the world's first Design Center dedicated to Design Thinking Principles, underscores our commitment to continuous and impactful innovation, addressing the ever-growing need for digital transformation. We proudly serve over 325+ customers worldwide, supported by a diverse workforce of solution architects and domain and technology experts in major global financial hubs. Summary: As an AI Engineer, you will work directly with clients to own the implementation of AI solutions using our AI platform. You will build and deploy end-to-end AI workflows, taking projects from concept to production, and solving complex, real-world challenges at scale. Your insights and learnings from client engagements will directly contribute to the evolution of our platform, ensuring we stay at the forefront of AI innovation. You will play a key role in expanding our presence into new markets and problem spaces unlocked by Generative AI. Key Responsibilities: Deliver Production-Ready AI Solutions: Design and deploy AI Agents, data processing pipelines, that are robust, scalable, and suitable for real-world applications. Solve Real Business Problems: Focus on practical AI solutions that address tangible business challenges, moving beyond theoretical approaches. Collaborate Across Teams: Work effectively with both technical and non-technical stakeholders to ensure clear communication and smooth project execution. Adapt in Dynamic Environments: Operate comfortably in fast-paced, evolving settings, adjusting quickly to shifting objectives and direct user feedback. Drive Innovation and Growth: Embrace an entrepreneurial mindset, continuously learning, innovating, and striving to make a high impact in a rapidly changing field. Client Interaction and Strategy Development: Engage with clients to understand their challenges, develop AI strategies, and translate their needs into actionable technical solutions. Deploying Solutions to Production: Move AI workflows from prototype to production, ensuring they integrate smoothly into client environments and solve real-world problems. Iterating and Improving: Continuously enhance deployed solutions based on feedback and evolving requirements, focusing on debugging, performance improvement, and workflow adaptation. Contributing to Platform Evolution: Share field insights to influence the development of new features and capabilities within the AI platform, aligning it with market needs. Key Traits: Technical Proficiency: Expertise in building and deploying AI models, data pipelines, and advanced analytics in production environments. Problem-Solver: Ability to design practical, impactful AI solutions that address real business challenges, focusing on tangible outcomes Collaborative: Effective communication skills to work with diverse teams, including technical and non-technical stakeholders, and explain complex AI concepts in understandable terms. Adaptable: Comfortable working in dynamic, fast-paced environments with evolving objectives, quickly iterating on solutions based on feedback. Innovative and Entrepreneurial: Passion for continuous learning, innovation, and applying an entrepreneurial approach to drive impact and growth. Client-Focused: Strong ability to engage directly with clients, understand their needs, and align AI strategies with business objectives. Detail-Oriented: Focus on refining, testing, and fine-tuning AI solutions for optimal performance in real-world settings. Continuous Learner: Commitment to staying updated on the latest AI technologies, tools, and methodologies, exploring new approaches to keep skills and solutions cutting-edge. Skills and Qualifications: Proven experience developing solutions using Generative AI models, with a strong understanding of the AI landscape and related technologies. Solid foundation in Machine Learning principles, including evaluation, training, and problem decomposition. Strong background in engineering or a related technical field such as Computer Science, Mathematics, Software Engineering, Physics, or Machine Learning. Proficiency in programming languages such as Python, Java, C++, JavaScript/TypeScript, or similar. Interested folks can reach out to bicky.nath@intellectdesign.com

Experience: 10+ years overall | Minimum 10 full-cycle AI/ML project implementations, including GenAI experience Role Summary: We are seeking a AI Architect to lead strategic AI transformation initiatives within the retail domain. This role demands deep hands-on experience in AI, Machine Learning (ML), and Generative AI (GenAI), along with the ability to engage directly with C-level stakeholders, align technical delivery with business objectives, and drive enterprise-wide adoption of advanced AI solutions.The ideal candidate is a techno-strategic leader who can take AI/ML/GenAI projects from ideation to productionbuilding architectures, leading cross-functional teams, and ensuring regulatory and operational alignment in retail environments.Key Responsibilities:Consulting & Business Alignment Partner with senior business and IT leadership, including CIOs, CDOs, and COOs, to identify high-impact use cases across e-commerce, retail operations, supply chain, and customer experience. Translate complex retail challenges into technically feasible and scalable AI/ML/GenAI solutions. Create strategic roadmaps, capability assessments, and PoV/PoC execution plans that align with business KPIs and regulatory needs. Solution Architecture & Delivery Leadership Design and lead delivery of AI/ML/GenAI pipelines covering data ingestion, model training, validation, deployment, and monitoring. Build and scale GenAI-based solutions like LLM-driven chatbots, intelligent product recommendation engines, RAG pipelines, summarization tools, and virtual assistants. Architect cloud-native AI platforms using AWS (SageMaker, Bedrock), Azure (ML, OpenAI), or GCP (Vertex AI, BigQuery, LangChain). Define and implement MLOps and LLMOps frameworks for versioning, retraining, CI/CD, and production observability. Ensure adherence to Responsible AI principles, including explainability, bias mitigation, auditability, and compliance with retail regulations (GDPR, CCPA, SOC2, etc.). Engineering & Integration Work closely with data engineering teams to acquire, transform, and pipeline data from retail systems, customer databases, inventory management systems, and real-time feeds. Design architecture for data lakes, feature stores, and vector databases supporting AI and GenAI use cases. Enable seamless integration of AI capabilities into enterprise workflows, customer platforms, and decision engines via APIs and microservices. Required Skills & Experience: 10+ years of experience in AI/ML, data engineering, and cloud architecture. Minimum of 5 end-to-end AI/ML project implementations from use case discovery through to productionization. Proven expertise in: (Any One) AI/ML frameworks: scikit-learn, XGBoost, TensorFlow, PyTorch GenAI/LLM platforms: OpenAI, Cohere, Mistral, LangChain, Hugging Face, vector DBs (Pinecone, FAISS, Chroma) Cloud platforms: AWS, Azure, GCP including AI/ML & GenAI native services MLOps/LLMOps tools: MLflow, Kubeflow, SageMaker Pipelines, Vertex AI Pipelines Strong experience with data security, governance, model risk management, and AI compliance frameworks relevant to retail. Ability to lead large cross-functional teams and engage both technical teams and senior stakeholders.