Role & responsibilities

- Build Python services that process, clean, and transform structured and unstructured finance data so AI applications can use it.
- Design and build RAG pipelines end to end. This covers document ingestion, chunking, embeddings, vector search, retrieval tuning, and grounded answers with source references.
- Build AI agents and multi-step workflows with LangChain and LangGraph, including tool calling, state handling, and human review steps where needed.
- Connect LLMs to internal APIs, databases, and lakehouse data so users can query and work with data in plain language.
- Test and evaluate LLM outputs for accuracy, relevance, and hallucinations, and use the results to improve quality.
- Monitor and improve the performance, latency, cost, and reliability of AI applications in production.
- Follow the security, access-control, and data-privacy practices required in a regulated financial workplace.
- Work with data engineers, product owners, and client stakeholders to turn business needs into working solutions, and document designs and decisions.

📌 AI Python Engineer- Bangalore and Mumbai- Immediate joiners
🏢 Anlage Infotech
📍 Mumbai