Gen AI Technical Lead

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 strong 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