Job Description Senior AI Engineer (Generative AI / Full-Stack / Architecture) Role Overview The Senior AI Engineer will lead the design, development, and deployment of enterprise-scale Generative AI solutions. This role involves ownership of system architecture, agentic workflow design, end-to-end GenAI pipelines, and high-performance backend services. The ideal candidate combines deep engineering expertise with hands-on experience in LLMs, scalable microservices, and modern software development practices. This position also includes mentoring engineers and driving engineering standards across teams. Key Responsibilities Generative AI Engineering & Architecture Lead the architecture, development, and production deployment of enterprise-grade Generative AI systems with a focus on scalability, reliability, and performance. Design and implement agentic workflows using LLMs, tools, and orchestration frameworks to enable intelligent autonomous behaviors. Build and integrate end-to-end GenAI pipelines, including model inference, RAG (Retrieval-Augmented Generation), embeddings, and application consumption via APIs. Collaborate with data and platform engineering teams to implement vector search, semantic retrieval, and contextual grounding for AI-driven responses. Full-Stack & Backend Engineering Apply strong full-stack engi neering skills to build user-facing GenAI applications and robust backend systems. Develop scalable microservices and secure RESTful APIs to expose AI and ML capabilities across enterprise applications. Integrate GenAI functions with front-end interfaces built using modern web technologies. Deployment, Operations, & Quality Lead model deployment, packaging, performance optimization, and lifecycle management in production environments. Ensure reliability and quality through test-driven development (TDD), reusable component design, and modern architectural principles. Drive CI/CD-based releases, containerized deployments, and DevOps practices for AI-driven applications. Collaboration & Leadership Provide technical mentorship to intermediate engineers and contribute to architectural design reviews. Champion engineering best practices, coding standards, and continuous improvement within Agile delivery teams. Required Skills & Technical Expertise Programming & Full-Stack Development Proficiency in Python, Java, R, and SQL. Frontend and full-stack development experience with ReactJS, HTML, CSS, and Node.js. AI / ML & Generative AI Hands-on experience with TensorFlow, Keras, and PyTorch. Strong foundations in Generative AI, NLP, and NLU. Expertise working with Large Language Models (LLMs) and prompt engineering. Agentic & GenAI Frameworks Experience with LangChain and familiarity with LangGraph and Ollama. Understanding of agentic system design, tool use, and workflow orchestration patterns. Retrieval & Knowledge Foundations Strong knowledge of vector databases, RAG pipelines, semantic search, and embedding techniques. Architecture, APIs & Microservices Demonstrated experience in microservices architecture, service-oriented design, and building scalable REST APIs. Expertise in API-driven development and integration patterns. Model Deployment & DevOps Experience with model packaging, containerization, deployment pipelines, and operational monitoring. Hands-on experience with GitHub, GitHub Actions, and CI/CD automation. Familiarity with both SQL and NoSQL databases. Preferred Qualifications Experience with cloud-based GenAI platforms (Azure OpenAI, AWS Bedrock, Google Vertex AI). Knowledge of distributed systems, high-availability architectures, and performance tuning. Prior experience leading technical initiatives or architectural decision-making. Soft Skills Strong leadership, communication, and mentoring capabilities. Ability to work across cross-functional teams in fast-paced Agile en vironments. Strategic thinking with the ability to translate business needs into scalable AI solutions. TCS does not use artificial intelligence tools for candidate screening or evaluation. This post is for a current vacancy. The hiring process includes an initial screening, followed by a technical evaluation and managerial discussion.