13 Cloud Ai Jobs

Cradlepoint is seeking a Senior Data Scientist to contribute to our efforts in artificial intelligence (AI) and automation technologies, aligning with our overall data strategy and business objectives. You will play a key leadership role in transforming raw data into actionable insights that drive business value. You will collaborate closely with cross-functional teams across the organization to identify key business challenges, design and implement innovative data-driven solutions, and effectively communicate your findings to both technical and non-technical audiences. What You Will Do: Key Responsibilities Partner with business stakeholders to understand their needs, translate them into technical requirements, and develop data-driven solutions. Communicate complex AI concepts to non-AI stakeholders (Data Domains, Enablers, etc.) and facilitate multi-functional collaboration. Establish and enforce data governance policies and procedures to ensure the ethical and responsible use of data in AI applications. Implement Objective Key Results to measure the performance and impact of AI and automation solutions and regularly report on the progress and success of AI initiatives to the Head of Data & AI. Lead and manage complex data science projects from inception to deployment, ensuring successful delivery and impact on business objectives. Develop, implement, and optimize machine learning models and algorithms to solve real-world business problems. Perform data cleaning, wrangling, and transformation to ensure data quality and prepare it for analysis. Conduct exploratory data analysis (EDA) to uncover hidden patterns, trends, and insights within data sets. Develop clear and concise data visualizations to effectively communicate complex findings to both technical and non-technical audiences. Stay up to date on the latest advancements in data science methodologies and tools, and actively seek opportunities to incorporate them into our practices. Mentor and guide junior data scientists within the team, fostering a collaborative and learning environment. The Skills You Bring: Required Qualifications Education: PhD in Statistics, Computer Science, Mathematics, or a related field; alternatively, a Master's or Bachelor's degree with significant work experience in the field. Experience: Proven track record of successfully leading and delivering data science projects with tangible business impact. AI/ML Expertise: Strong expertise in LLM (Large Language Models), deep learning, machine learning algorithms (e.g., supervised learning, unsupervised learning, reinforcement learning), and statistical modeling. Programming & Big Data: Proficiency in programming languages such as Python, R , and familiarity with big data processing tools (e.g., Spark, Hadoop) is a plus. Cloud AI Solutions: Familiarity in developing and deploying End-to-End (E2E) AI solutions in cloud platforms (Azure, AWS, GCP). Communication & Collaboration: Excellent communication and collaboration skills, with the ability to effectively translate complex technical concepts to a non-technical audience. Problem-Solving: Strong problem-solving skills and a passion for applying data science techniques to solve real-world problems. Work Management: Ability to work independently and manage multiple projects simultaneously while meeting deadlines.

We are hiring an AI Solution Architect with 12-15 years of experience in software development and architecture, with deep expertise in AI/ML within the healthcare IT domain. This is a 12-month full-time onsite role based in Chennai or Hyderabad for an immediate joiner. The ideal candidate will possess strong experience in cloud platforms (GCP preferred), AI/ML frameworks (TensorFlow, PyTorch, Scikit-learn), and compliance with healthcare industry standards (e.g., HIPAA). Youll be responsible for designing scalable AI solutions, leading cross-functional teams, mentoring developers, and driving end-to-end AI solution delivery using MLOps best practices.

As a Solution Architect/Business Development Manager at NTT DATA, you will play a crucial role in specializing in Hyperscalers and cloud-based AI services, particularly Large Language Models (LLMs) offered by major cloud providers. Your responsibilities will include assessing client needs, recommending appropriate cloud AI technologies, sizing opportunities and cloud infrastructure requirements, and collaborating with delivery teams to create end-to-end solutions with accurate costing. You will need to demonstrate deep expertise in cloud-based AI services such as AWS Bedrock, Azure OpenAI Service, Google Vertex AI, and their supported models. Your key roles and responsibilities will include solution architecture & technical leadership, business development, project & delivery leadership, and AI agent development. You will be required to develop compelling proposals and solution presentations for cloud-based AI implementations, nurture client relationships, and lead technical discovery sessions with clients. Additionally, you will need to architect multi-agent systems that leverage cloud platform capabilities, develop frameworks for agent orchestration and governance, and design cloud-native agent solutions that integrate with existing enterprise systems. To be successful in this role, you should have at least 8 years of experience in solution architecture or technical consulting roles, with 3 years of specialized experience working with LLMs and Private AI solutions. A strong understanding of cloud infrastructure sizing, optimization, and cost management for AI workloads is essential, along with the ability to convert business requirements into technical specifications. A bachelor's degree in computer science, AI, or a related field is required, and the ability to travel up to 25% may be necessary. Preferred qualifications include a master's degree or PhD in Computer Science or a related technical field, as well as cloud certifications such as AWS Certified Solutions Architect, Microsoft Certified: Azure Solutions Architect Expert, and Google Cloud Professional Cloud Architect. Experience with autonomous agent development using cloud-based AI services, deploying and fine-tuning LLMs on cloud platforms, and prompt engineering and LLM optimization techniques is also desirable. Strong problem-solving abilities, excellent communication skills, and an analytical mindset are essential for this role. This position is based in Delhi or Bangalore and offers a hybrid working environment. NTT DATA is a trusted global innovator of business and technology services, serving 75% of the Fortune Global 100. With a commitment to helping clients innovate, optimize, and transform for long-term success, NTT DATA invests over $3.6 billion each year in R&D. As a Global Top Employer, NTT DATA has diverse experts in more than 50 countries and offers services including business and technology consulting, data and artificial intelligence, industry solutions, application development, infrastructure management, and connectivity.,

As a Data Scientist at our company, you will be at the forefront of AI innovation, focusing on Agentic AI, cloud-based AI services, and immersive experiences in AR/VR. You will have the opportunity to work on cutting-edge projects spanning various industries such as retail, healthcare, gaming, and enterprise tech. Your main responsibilities will include building, deploying, and optimizing AI/ML models with a specific focus on Agentic AI and multi-agent coordination frameworks. You will also utilize Google Cloud AI and Azure AI Services for scalable training, inference, and deployment. Additionally, you will apply Computer Vision techniques for object detection, image classification, and spatial tracking in AR/VR settings. Collaboration with product, engineering, and design teams will be essential to bring AI-driven AR/VR applications to fruition. Experience with Multi-Cloud Pipelines for managing workflows in a hybrid cloud environment is required. You will be expected to continuously explore and experiment with emerging AI techniques in areas such as generative agents, prompt engineering, and memory-based systems. To excel in this role, you must possess at least 3-5 years of hands-on experience in AI/ML model development and deployment. Strong proficiency in Python and familiarity with frameworks like TensorFlow, PyTorch, or OpenCV are essential skills for success in this position. Join us in shaping the future of AI and immersive technologies across diverse industries, and be part of our dynamic team that is driving innovation forward.,

As a Data Scientist at Agentic AI | Cloud AI | AR/VR, you will play a crucial role in working on cutting-edge innovation across various verticals such as retail, healthcare, gaming, and enterprise tech. Your primary responsibility will be to build, deploy, and optimize AI/ML models with a specific focus on Agentic AI and multi-agent coordination frameworks. You will utilize Google Cloud AI and Azure AI Services for scalable training, inference, and deployment, while also applying Computer Vision techniques for object detection, image classification, and spatial tracking in AR/VR contexts. Collaboration will be key in this role, as you will work closely with product, engineering, and design teams to bring AI-driven AR/VR applications to life. Additionally, you will be responsible for utilizing Multi-Cloud Pipelines for managing end-to-end workflows in a hybrid cloud setup, and continuously experimenting with emerging AI techniques in the realm of generative agents, prompt engineering, and memory-based systems. To excel in this role, you must possess at least 3-5 years of hands-on experience in AI/ML model development and deployment. Strong Python skills are essential, along with experience in frameworks like TensorFlow, PyTorch, or OpenCV. If you are passionate about exploring the next frontier of AI and eager to contribute to groundbreaking projects in the field of Agentic AI, Cloud AI, and AR/VR, then this opportunity is perfect for you.,

Gen AI Specialist Exp: 10+ Yrs Location: Bengaluru We are seeking a visionary and driven leader to spearhead our organization's transformative journey into the world of Generative AI. This individual will play a pivotal role in building and scaling our Gen AI capabilities, fostering a culture of innovation, and driving tangible productivity gains across all departments. The ideal candidate is a passionate advocate for AI with a proven track record of successfully implementing and scaling AI/ML initiatives within an enterprise setting. Responsibilities: Develop and Implement Gen AI Strategy: Identify key opportunities and use cases for Gen AI across various business functions. Establish and track clear goals, metrics, and KPIs to measure the success of Gen AI initiatives. Workforce Training and Enablement: Design and deliver comprehensive training programs to upskill the workforce on Generative AI concepts, tools, and best practices. Foster a culture of learning and experimentation with Gen AI technologies with Hackathons or ideathons Create resources and support systems to empower employees to leverage Gen AI in their daily work. Build and Manage a Gen AI Repository: Establish a centralized repository of reusable Gen AI components, models, and tools. Develop and enforce standards and guidelines for the development and deployment of Gen AI solutions. Ensure the repository is easily accessible and promotes knowledge sharing across the organization. Drive Productivity and Innovation: Work closely with business units to identify and prioritize high-impact Gen AI use cases. Monitor and analyze the impact of Gen AI on productivity, efficiency, and business outcomes. Stay Ahead of the Curve: Continuously research and evaluate emerging Gen AI technologies, trends, and best practices. Identify and recommend new tools and platforms to enhance the organization's Gen AI capabilities. Represent the organization at industry events and conferences. Qualifications: Education: Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related field. Experience: 10+ years of experience in the technology industry with a focus on AI/ML. Proven track record of successfully leading and implementing AI/ML initiatives in an enterprise environment. Experience with building and managing Gen AI models and solutions. Strong understanding of various Gen AI techniques, including large language models (LLMs), natural language processing (NLP), and computer vision. Skills: Excellent leadership, communication, and interpersonal skills. Strong analytical and problem-solving abilities. Ability to effectively collaborate with cross-functional teams. Passion for driving innovation and staying ahead of technology trends. Desirable Experience: Experience with cloud-based AI platforms (e.g., Google Cloud AI, AWS AI, Azure AI). Familiarity with agile development methodologies. Contributions to the AI community (e.g., publications, open-source projects).

Cloud, Artificial Intelligence, Data Engineering Skill to Evaluate : Cloud, Artificial Intelligence, Data Engineering Experience : 6 to 10 Years Location : Bengaluru Job Description : Job Summary: We are looking for an experienced Cloud AI and Data Engineer with a strong background in cloud-native data solutions, AI/ML engineering, and emerging Generative AI (GenAI) technologies. The ideal candidate will have 68 years of hands-on experience in building robust data platforms, deploying scalable ML models, and integrating GenAI solutions across cloud environments. Key Responsibilities: Build and maintain scalable data pipelines and infrastructure for AI and analytics using cloud-native tools (e.g., AWS Glue, Azure Data Factory, GCP Dataflow) Design and implement production-ready GenAI applications using services like Amazon Bedrock , Azure OpenAI , or Google Vertex AI Develop and deploy AI/ML models including transformer-based and LLM (Large Language Model) solutions Integrate GenAI with enterprise workflows using APIs, orchestration layers, and retrieval-augmented generation (RAG) patterns Collaborate with data scientists, product managers, and platform teams to operationalize AI-driven insights and GenAI capabilities Build prompt engineering frameworks, evaluate output quality, and optimize token usage and latency for GenAI deployments Set up monitoring, drift detection, and governance mechanisms for both traditional and GenAI models Implement CI/CD pipelines for data and AI solutions with automated testing and rollback strategies Ensure cloud solutions adhere to data privacy, security, and regulatory compliance standards Required Skills & Qualifications: 68 years of experience in data engineering or machine learning engineering in cloud environments (AWS, Azure, or GCP) Proficiency in Python and SQL; familiarity with PySpark, Java, or Scala is a plus Experience working with GenAI models such as GPT, Claude, or custom LLMs via cloud services (e.g., Bedrock, Azure OpenAI, HuggingFace) Hands-on with prompt design, fine-tuning, vector stores (e.g., FAISS, Pinecone), and knowledge base integrations Experience with MLOps and LLMOps tools (e.g., MLflow, LangChain, SageMaker Pipelines, Weights & Biases) Solid understanding of containerization (Docker), orchestration (Kubernetes), and microservices Knowledge of data lake/warehouse platforms such as S3, Snowflake, BigQuery, or Redshift Familiar with governance frameworks, access control, and responsible AI practices Preferred Qualifications: Certifications in Cloud AI/ML platforms (e.g., AWS Certified Machine Learning, Azure AI Engineer) Experience building RAG systems, vector database search, and multi-turn conversational agents Exposure to real-world GenAI use cases like code generation, chatbots, document summarization, or knowledge extraction Knowledge of OpenAPI, JSON schema validation, and API lifecycle tools

Job Title: LLM Lead Experience: 6+ years Location: Bangalore / Pune / Gurgaon Contractual - 6months Job Description: Looking for a skilled Development Lead with expertise in Generative AI and Large Language models. As a Lead, you will play a key role in developing cutting-edge LLM applications and systems for our clients. The ideal candidate will have a strong technical background and a passion for pushing the boundaries of LLM apps. Responsibilities : Develop and extend digital products and creative applications, leveraging LLM technologies at their core. Lead a product development and product operations team to further develop, enhance and extend existing digital products built on top of LLMs Lead client onboarding, client rollout, and client adoption efforts , maximizing use of the product across multiple clients Lead enhancements and extensions for client specific capabilities and requests Successful leadership and delivery of projects involving Cloud Gen-AI Platforms and Cloud AI Services, Data Pre-processing, Cloud AI PaaS Solutions, LLMs Ability to work with Base Foundation LLM Models, Fine Tuned LLM models, working with a variety of different LLMs and LLM APIs. Must-Have: A minimum of 6+ years of experience is required, and candidates should have spent at least 23 years in GenAI and LLM projects . Strong Expertise in Python development, and the Python Dev ecosystem. hands-on experience in working with Large Language Model. Experience with multiple LLMs and models - including Azure OpenAI GPT model family primarily, but also Google Gemini, Anthropic Claude, etc. Experience in Cloud Gen-AI platforms, services, and APIs, primarily Azure OpenAI . Hands-on experience working with RAG pipelines and Enterprise technologies and solutions / frameworks - including LangChain, Llama Index, etc. Experience with vector databases (Azure AI Search, AWS Kendra, FAISS, Milvus etc.). Experience with Automation Workflows and building Automation solutions to facilitate rapid onboarding for digital products

Senior Full Stack Developer Experience: 3-5 Years Exp Salary : 15 to 25 LPA Preferred Notice Period: Within 30 Days Shift: 10:00AM to 7:00PM IST Opportunity Type: Hybrid (Pune) Placement Type: Permanent (*Note: This is a requirement for one of Uplers' Clients) Must have skills required : Generative AI, Cloud AI Services, Architecture Inferenz(One of Uplers' Clients) is Looking for: Senior Full Stack Developer who is passionate about their work, eager to learn and grow, and who is committed to delivering exceptional results. If you are a team player, with a positive attitude and a desire to make a difference, then we want to hear from you. About Inferenz At Inferenz, our team of innovative technologists and domain experts help accelerating the business growth through digital enablement and navigating the industries with data, cloud and AI services and solutions. We dedicate our resources to increase efficiency and gain a greater competitive advantage by leveraging various next generation technologies. Our technology expertise has helped us delivering the innovative solutions in key industries such as Healthcare & Life Sciences, Consumer & Retail, Financial Services and Emerging industries. About The Role: Job Description: Role Overview: We are seeking an experienced Senior Full Stack Developer to join our team building innovative Generative AI (GenAI) based applications. The ideal candidate will have a strong background in developing scalable RESTful APIs using Python, as well as modern frontend applications with Node.js or React. Experience with cloud platforms (Azure or AWS), Kubernetes, microservices architecture, and version control (Git or Azure Repos) is essential. Familiarity with AI/ML/GenAI technologies and Agenting AI is highly valued. Key Responsibilities: Full-Stack Development: Design, build, and maintain scalable RESTful APIs using Python and frontend applications using Node.js or React. GenAI Integration: Develop and optimize Agenting AI components using Python, ensuring seamless integration with backend services. Cloud Deployment: Manage application deployment, scaling, and monitoring on Azure or AWS using Kubernetes and microservices architecture. Collaboration: Work with cross-functional teams using Jira and Confluence for project tracking and documentation. Performance Optimization: Ensure high availability, security, and efficiency of applications through robust coding practices and infrastructure management. Required Skills & Experience: Backend: Strong expertise in Python and REST API development. Frontend: Proficiency in Node.js, React, and modern JavaScript frameworks. Cloud & DevOps: Hands-on experience with Azure or AWS, Kubernetes, microservices, and Git or Azure Repos for version control. Tools: Familiarity with Jira, Confluence, and CI/CD pipelines. Experience: 5+ years in full-stack development with production-grade applications. Preferred Skills: AI/ML Knowledge: Understanding of GenAI tools (e.g., LangChain, LLMs, RAG/GraphRAG/MCP architectures) and Agenting AI development. Cloud AI Services: Experience with cloud-based AI platforms (e.g., AWS Bedrock, Azure AI). Architecture: Proficiency in designing scalable systems and troubleshooting distributed environments. What We Offer: Competitive salary and comprehensive benefits package. Flexible work hours and a hybrid working model to support work-life balance. Opportunities for professional growth and development in a cutting-edge technology environment. Exposure to Generative AI and other advanced technologies. Inferenz is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. How to apply for this opportunity: Easy 3-Step Process: 1. Click On Apply! And Register or log in on our portal 2. Upload updated Resume & Complete the Screening Form 3. Increase your chances to get shortlisted & meet the client for the Interview! About Our Client: At Inferenz, our team of innovative technologists and domain experts help accelerating the business growth through digital enablement and navigating the industries with data, cloud and AI services and solutions. We dedicate our resources to increase efficiency and gain a greater competitive advantage by leveraging various next generation technologies. Our technology expertise has helped us delivering the innovative solutions in key industries such as Healthcare & Life Sciences, Consumer & Retail, Financial Services and Emerging industries.. About Uplers: Our goal is to make hiring and getting hired reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant product and engineering job opportunities and progress in their career. (Note: There are many more opportunities apart from this on the portal.) So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you!

Key Responsibilities Architecture Development Define and implement AI architecture for enterprise applications. Develop AI frameworks and models that integrate with existing enterprise systems . Ensure AI solutions are scalable, secure, and compliant with data privacy regulations (GDPR, CCPA, etc.) . Technical Leadership & Innovation Architect AI-powered platforms that support Gen-AI & AI frameworks and models. Stay ahead of AI advancements and drive innovation in AI-driven automation, personalization, and optimization . AI Model Development & Optimization Execute the training, fine-tuning, and deployment of LLMs and ML models. Optimize model performance using techniques such as prompt engineering, retrieval-augmented generation (RAG), and knowledge distillation . Implement MLOps and AIOps best practices for continuous model monitoring and improvement. Cloud & Infrastructure Integration Design and deploy AI solutions on Azure AI, AWS SageMaker, Google Vertex AI, or OpenAI services . Ensure AI applications are cloud-native, containerized (Docker, Kubernetes), and scalable . Implement data pipelines, feature stores, and vector databases for efficient AI processing. Cross-Functional Collaboration Work closely with engineering, data science, product, and business teams to align AI initiatives with company goals. Provide technical mentorship and guidance to AI engineers and developers. Communicate AI strategy and roadmaps to senior leadership and stakeholders. Security, Compliance & Responsible AI Ensure AI solutions adhere to ethical AI principles, bias mitigation, and fairness . Implement AI governance frameworks for explainability, accountability, and security. Address risks related to AI hallucinations, adversarial attacks, and regulatory compliance . Qualifications Educational qualification: B-Tech / M-Tech Computer Science preferred Experience : 10+ Years Mandatory/requires Skills : Core AI & GenAI Expertise Strong hands-on experience with LLMs (GPT, Llama, Claude, etc.), ML frameworks (TensorFlow, PyTorch, Hugging Face), and deep learning models . Expertise in GenAI applications, including chatbots, code generation, multimodal AI, and synthetic data generation . Experience with RAG, vector databases (FAISS, Pinecone, Weaviate), and embeddings . Proficiency in AI-driven knowledge management, summarization, and automation . Software Architecture & Engineering Strong understanding of enterprise software architectures, microservices, APIs, and distributed computing . Hands-on experience with Python, Java, Go, or other relevant languages . Familiarity with GraphQL, REST APIs, and event-driven architectures . Experience with MLOps pipelines, CI/CD for AI, and automated AI workflows . Cloud & DevOps Expertise in deploying AI models on Azure, AWS, or Google Cloud . Experience with serverless AI architecture, Kubernetes, and cloud-native AI . Knowledge of data engineering, data lakes, and streaming analytics for AI . Preferred Skills : Leadership & Communication Ability to translate complex AI concepts into business-friendly insights. Strong stakeholder management, presentation, and decision-making skills.

Join a company that is pushing the boundaries of what is possible. We are renowned for our technical excellence and leading innovations, and for making a difference to our clients and society. Our workplace embraces diversity and inclusion its a place where you can grow, belong and thrive. Your day at NTT DATA We are seeking a talented AI/GenAI Engineer to join our team in delivering cutting-edge AI solutions to clients. The successful candidate will be responsible for implementing, developing, and deploying AI/GenAI models and solutions on cloud platforms. This role requires knowledge of ServiceNow modules like CSM and virtual agent development. Candidate should have strong technical aptitude, problem-solving skills, and the ability to work effectively with clients and internal teams. What youll be doing Key Responsibilities: Cloud AI Implementation: Implement and deploy AI/GenAI models and solutions using various cloud platforms (e.g., AWS SageMaker, Azure ML, Google Vertex AI) and frameworks (e.g., TensorFlow, PyTorch, LangChain, Vellum). Build Virtual Agent in SN Design, develop and deploy virtual agents using SN agent builder Integrate SN Design and develop seamless integration of SN with other external AI systems Agentic AI: Assist in developing agentic AI systems on cloud platforms, enabling autonomous decision-making and action-taking capabilities in AI solutions. Cloud-Based Vector Databases: Implement cloud-native vector databases (e.g., Pinecone, Weaviate, Milvus) or cloud-managed services for efficient similarity search and retrieval in AI applications. Model Evaluation and Fine-tuning: Evaluate and optimize cloud-deployed generative models using metrics like perplexity, BLEU score, and ROUGE score, and fine-tune models using techniques like prompt engineering, instruction tuning, and transfer learning. Security for Cloud LLMs: Apply security practices for cloud-based LLMs, including data encryption, IAM policies, and network security configurations. Client Support Support client engagements by implementing AI requirements and contributing to solution delivery. Cloud Solution Implementation: Build scalable and efficient cloud-based AI/GenAI solutions according to architectural guidelines. Cloud Model Development: Develop and fine-tune AI/GenAI models using cloud services for specific use cases, such as natural language processing, computer vision, or predictive analytics. Testing and Validation Conduct testing and validation of cloud-deployed AI/GenAI models, including performance evaluation and bias detection. Deployment and Maintenance Deploy AI/GenAI models in production environments, ensuring seamless integration with existing systems and infrastructure. Cloud Deployment Deploy AI/GenAI models in cloud production environments and integrate with existing systems. Education Bachelor/Masters in Computer Science, AI, ML, or related fields. Experience 3-5 years of experience in engineering solutions, with a track record of delivering Cloud AI solutions. . Should have at least 2 years experience of SN and SN agent builder Technical Skills: Proficiency in cloud AI/GenAI services and technologies across major cloud providers (AWS, Azure, GCP) Experience with cloud-native vector databases and managed similarity search services Experience with SN modules like CSM and virtual agent builder Experience with security measures for cloud-based LLMs, including data encryption, access controls, and compliance requirements Programming Skills: Strong programming skills in languages like Python or R Cloud Platform Knowledge: Strong understanding of cloud platforms, their AI services, and best practices for deploying ML models in the cloud Communication Excellent communication and interpersonal skills, with the ability to work effectively with clients and internal teams. Problem-Solving Strong problem-solving skills, with the ability to analyse complex problems and develop creative solutions. Nice to have: Experience with serverless architectures for AI workloads Nice to have: Experience with ReactJS for rapid prototyping of cloud AI solution frontends Location: Delhi or Bangalore (with remote work options)

Your day at NTT DATA Cloud AI/GenAI Engineer(ServiceNow) We are seeking a talented AI/GenAI Engineer to join our team in delivering cutting-edge AI solutions to clients. The successful candidate will be responsible for implementing, developing, and deploying AI/GenAI models and solutions on cloud platforms. This role requires knowledge of ServiceNow modules like CSM and virtual agent development. Candidate should have strong technical aptitude, problem-solving skills, and the ability to work effectively with clients and internal teams. What youll be doing Key Responsibilities: Cloud AI Implementation: Implement and deploy AI/GenAI models and solutions using various cloud platforms (e.g., AWS SageMaker, Azure ML, Google Vertex AI) and frameworks (e.g., TensorFlow, PyTorch, LangChain, Vellum). Build Virtual Agent in SN Design, develop and deploy virtual agents using SN agent builder Integrate SN Design and develop seamless integration of SN with other external AI systems Agentic AI: Assist in developing agentic AI systems on cloud platforms, enabling autonomous decision-making and action-taking capabilities in AI solutions. Cloud-Based Vector Databases: Implement cloud-native vector databases (e.g., Pinecone, Weaviate, Milvus) or cloud-managed services for efficient similarity search and retrieval in AI applications. Model Evaluation and Fine-tuning: Evaluate and optimize cloud-deployed generative models using metrics like perplexity, BLEU score, and ROUGE score, and fine-tune models using techniques like prompt engineering, instruction tuning, and transfer learning. Security for Cloud LLMs: Apply security practices for cloud-based LLMs, including data encryption, IAM policies, and network security configurations. Client Support Support client engagements by implementing AI requirements and contributing to solution delivery. Cloud Solution Implementation: Build scalable and efficient cloud-based AI/GenAI solutions according to architectural guidelines. Cloud Model Development: Develop and fine-tune AI/GenAI models using cloud services for specific use cases, such as natural language processing, computer vision, or predictive analytics. Testing and Validation Conduct testing and validation of cloud-deployed AI/GenAI models, including performance evaluation and bias detection. Deployment and Maintenance Deploy AI/GenAI models in production environments, ensuring seamless integration with existing systems and infrastructure. Cloud Deployment Deploy AI/GenAI models in cloud production environments and integrate with existing systems. Education Bachelor/Masters in Computer Science, AI, ML, or related fields. Experience 3-5 years of experience in engineering solutions, with a track record of delivering Cloud AI solutions. . Should have at least 2 years experience of SN and SN agent builder Technical Skills: Proficiency in cloud AI/GenAI services and technologies across major cloud providers (AWS, Azure, GCP) Experience with cloud-native vector databases and managed similarity search services Experience with SN modules like CSM and virtual agent builder Experience with security measures for cloud-based LLMs, including data encryption, access controls, and compliance requirements Programming Skills: Strong programming skills in languages like Python or R Cloud Platform Knowledge: Strong understanding of cloud platforms, their AI services, and best practices for deploying ML models in the cloud Communication Excellent communication and interpersonal skills, with the ability to work effectively with clients and internal teams. Problem-Solving Strong problem-solving skills, with the ability to analyse complex problems and develop creative solutions. Nice to have: Experience with serverless architectures for AI workloads Nice to have: Experience with ReactJS for rapid prototyping of cloud AI solution frontends Location: Delhi or Bangalore (with remote work options)

Key Responsibilities: Cloud AI Design and Development: Design, develop, and deploy AI/GenAI models and solutions using various cloud platforms (e.g., AWS SageMaker, Azure ML, Google Vertex AI) and frameworks (e.g., TensorFlow, PyTorch, LangChain, Vellum). Agentic AI: Develop and integrate agentic AI systems on cloud platforms, enabling autonomous decision-making and action-taking capabilities in AI solutions. Cloud-Based Vector Databases: Design and implement cloud-native vector databases (e.g., Pinecone, Weaviate, Milvus) or cloud-managed services for efficient similarity search and retrieval in AI applications. Model Evaluation and Fine-tuning: Evaluate and optimize cloud-deployed generative models using metrics like perplexity, BLEU score, and ROUGE score, and fine-tune models using techniques like prompt engineering, instruction tuning, and transfer learning. Security for Cloud LLMs: Implement robust security measures for cloud-based LLMs, including data encryption, IAM policies, network security, model watermarking, and compliance with cloud security best practices. Technical Leadership: Provide technical guidance and support to junior team members on cloud AI implementation, ensuring high-quality deliverables and adherence to best practices. Client Engagement: Collaborate with clients to understand their AI requirements, develop tailored solutions, and deliver high-quality results. Cloud Solution Architecture: Design scalable, efficient, and cost-effective cloud-based AI/GenAI architectures, considering factors like data quality, model performance, and serverless/container-based deployment options. Cloud Model Development: Develop and fine-tune AI/GenAI models using cloud services for specific use cases, such as natural language processing, computer vision, or predictive analytics. Testing and Validation: Ensure thorough testing and validation of AI/GenAI models, including performance evaluation, bias detection, and explainability. Deployment and Maintenance: Deploy AI/GenAI models in production environments, ensuring seamless integration with existing systems and infrastructure. Knowledge Sharing: Share knowledge and expertise with the team, contributing to the development of best practices and staying up-to-date with industry trends. Requirements: Education: Bachelor/Master's in Computer Science, AI, ML, or related fields. Experience: 8+ years of experience in engineering solutions, with a track record of delivering Cloud AI solutions. Technical Skills: Proficiency in cloud AI/GenAI services and technologies across major cloud providers (AWS, Azure, GCP) Experience with cloud-native vector databases and managed similarity search services Experience with security measures for cloud-based LLMs, including data encryption, access controls, and compliance requirements Programming Skills: Strong programming skills in languages like Python or R Cloud Platform Knowledge: Strong understanding of cloud platforms, their AI services, and best practices for deploying ML models in the cloud Communication: Excellent communication and interpersonal skills, with the ability to work effectively with clients and internal teams. Problem-Solving: Strong problem-solving skills, with the ability to analyse complex problems and develop creative solutions. Nice to have: Experience with serverless architectures for AI workloads Nice to have: Experience with ReactJS for rapid prototyping of cloud AI solution frontends