- Evaluate LLMs and agent frameworks for performance, cost, and use case suitability.

Job Summary :

We are seeking an experienced Senior Python Engineer with strong expertise in GenAI, RAG pipelines, and agent-based systems. The ideal candidate will have a deep foundation in Python and microservices architectures, hands-on experience with modern LLM frameworks, and the ability to design, develop, and optimize production-grade AI applications.

Key Responsibilities :

- Design, develop, and maintain scalable Python-based services for GenAI applications.

- Build and tune Retrieval-Augmented Generation (RAG) pipelines, including data ingestion, embeddings, vector storage, and retrieval logic.

- Implement and optimize agent-based workflows using frameworks such as LangChain, LangGraph, CrewAI, or similar.

- Develop intelligent RAG-based search solutions with optimized retrieval and ranking strategies.

- Evaluate and select LLMs and agent frameworks based on performance, cost, latency, and use-case requirements.

- Architect and implement microservices-based systems for AI workloads.

- Collaborate with product, data, and platform teams to translate requirements into technical solutions.

- Ensure best practices in code quality, system reliability, scalability, and security.

- Conduct performance tuning, monitoring, and troubleshooting of AI pipelines.

Required Skills & Qualifications :

- 7- 9 years of hands-on experience in Python development.

- Strong foundation in Python programming and microservices architectures.

- Hands-on experience with LangChain, LangGraph, CrewAI, or similar GenAI frameworks.

- Practical experience working with LLMs and agent-based architectures.

- Proven experience developing and tuning RAG pipelines.

- Strong knowledge of embeddings, vector databases, and intelligent retrieval systems.

- Experience in data ingestion pipelines and retrieval optimization.