Experience Level: Minimum 7-10 years of total IT experience (at least 2+ years in Generative AI, LLMs, or related AI/ML technologies)

- Should have strong technical expertise in Python, hands-on experience with at least one GenAI framework (LangGraph, LangChain, or Google AI Development Kit), and solid working knowledge of one hyperscaler platform (Google Cloud, Azure, or AWS).
- The associate should lead solution design, integrating LLMs into enterprise workflows, mentoring team members, and driving production-grade implementation of GenAI use cases.
- Good knowledge of MLOps or DevOps teams to automate model deployment, versioning, and monitoring.

Key Responsibilities:

1. Solution Design

- Design, architect, and implement Generative AI workflows and agents using frameworks such as LangChain, LangGraph, or Google ADK.
- Integrate LLMs (e.g., Llama, Gemini, GPT, Claude) into enterprise systems and custom applications.
- Define and implement retrieval-augmented generation (RAG) pipelines using vector databases (e.g., ChromaDB, Pinecone, FAISS, Weaviate, Vertex AI Matching Engine).
- Architect scalable and secure GenAI microservices leveraging cloud-native components.

2. Development & Implementation

- Lead Python-based development efforts for building prompt orchestration, tool agents, and data pipelines.
- Develop and deploy APIs or microservices integrating LLMs with enterprise data sources.
- Implement prompt optimization, context management, and model performance tuning.

3. Cloud Integration

- Architect, deploy, and monitor GenAI workloads on one hyperscaler:
- GCP (Vertex AI, Document AI, AlloyDB, BigQuery, Cloud Run)
- Azure (OpenAI Service, Cognitive Search, Azure ML)




- AWS (Bedrock, SageMaker, Lambda, API Gateway)

- Manage cloud infrastructure for scaling AI models, ensuring cost efficiency and compliance.

4. Leadership & Mentoring

- Lead a small team of AI engineers and developers.
- Conduct code reviews, enforce best practices, and mentor junior engineers.
- Collaborate closely with product owners, data engineers, and business stakeholders to translate business needs into technical requirements.
- Contribute to internal GenAI capability building and reusable assets for the organization.

Required Skills & Experience:

1. Core Technical Skills

- Python (advanced proficiency; ability to build APIs, pipelines, and modular frameworks).
- Hands-on with at least one GenAI framework:
- LangChain, LangGraph, or Google ADK (AI Development Kit).
- Expertise with LLM integration (OpenAI API, Gemini API, Ollama, Hugging Face, etc.).
- Experience with RAG, embeddings, and vector databases.
- Familiarity with PEFT, LoRA, or prompt fine-tuning approaches.
- Cloud / Hyperscaler Expertise (at least one required)
- Google Cloud Platform (GCP) Vertex AI, Document AI, BigQuery, AlloyDB, Cloud Run, IAM
- Azure – Azure OpenAI, Cognitive Search, Azure ML, Azure Functions
- AWS – Bedrock, SageMaker, Lambda, API Gateway, DynamoDB

2. Other Desirable Skills

- Knowledge of REST APIs, JSON, and FastAPI/Flask frameworks.
- Familiarity with data governance, PII handling, and AI ethics principles.
- Understanding of Docker/Kubernetes, CI/CD, and Git-based version control.
- Exposure to front-end integration with AI chat agents (React, Streamlit, Gradio, etc.) is a plus.

3. Location:

- Offshore, open to all TCS ODC located areas

📌 Gen AI Technical Lead (India)
🏢 Tata Consultancy Services
📍 India