Walk-in || Generative AI

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 (FAST 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.

1. 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).

1. Cloud Integration

• Assist in deploying workloads to one hyperscaler (GCP, Azure, or AWS) under guidance: o GCP: Vertex AI, Cloud Run basics