3 to 10 Years of experience using Python.

- Strong proficiency in Python and experience with relevant libraries and frameworks (e.g., pandas, LangChain, LangGraph).
- Strong experience working with API calls (QUICK API, Rest API)
- Proficiency with LLM integrations
- At least one project is live in production
- Ability to work efficiently within a fast-paced, deadline-driven environment, prioritize tasks, manage time effectively, and communicate challenges or issues proactively
- Good to have experience working using MCP servers. Development & Implementation
- Implement Python modules for data ingestion, prompt orchestration, and basic tool-agent workflows.
- Build REST APIs/microservices (FastAPI/Flask) to connect LLMs with enterprise data sources.
- Assist in developing Retrieval-Augmented Generation (RAG) components: ingestion, embeddings, chunking, and retrieval

. • Configure and integrate LLMs (OpenAI, Gemini, Claude, Llama,



Mistral) via APIs or SDKs.
- Write unit/integration tests; contribute to robust error handling and logging.
- Support feature deployment and troubleshoot issues in staging/production. 2. Data & Model Ops
- Prepare datasets, metadata, and embeddings using vector databases (FAISS, Chroma, Pinecone, Weaviate).
- Participate in evaluating model outputs; assist with prompt optimization and context management.
- Help maintain experiment tracking and model/version metadata using MLOps tools (e.g., MLflow).
- Contribute to metrics dashboards (latency, token usage, cost, accuracy). 3. Cloud Integration
- Assist in deploying workloads to one hyperscaler (GCP, Azure, or AWS) under guidance: o GCP: Vertex AI, Cloud Run basics

📌 Gen AI (Bengaluru)
🏢 Tata Consultancy Services
📍 Bengaluru