Generative AI Engineer

Job Summary

We are looking for an experienced  Generative AI Engineer / Technical Lead  to design and develop enterprise AI solutions, with a focus on  Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents and financial document intelligence.

The role involves developing scalable AI applications and backend services, integrating LLM technologies with enterprise systems, and providing technical leadership for AI engineering initiatives.

Key Responsibilities

Design and develop  Generative AI and RAG-based applications  for enterprise and financial document use cases.

Develop  AI agents and agentic workflows  using LangChain, LangGraph or similar frameworks.

Build retrieval solutions using  embeddings, vector databases, semantic search, reranking and contextual retrieval.

Develop AI-powered solutions for  financial document analysis, comparison, validation and information extraction.

Integrate LLM platforms including  OpenAI, Claude, Llama and AWS Bedrock.

Implement AI evaluation, observability and safety mechanisms to improve response accuracy and reduce hallucinations.

Develop scalable backend services and APIs using  Python, FastAPI and microservices architecture.

Work with  PostgreSQL, MongoDB, Redis and vector databases.

Deploy and manage applications using  AWS, Docker and Kubernetes.

Develop CI/CD pipelines and follow software engineering practices including testing, code quality and version control.

Provide technical guidance and mentorship to engineering team members.

Collaborate with product and business teams to translate requirements into scalable AI solutions.

Requirements

Minimum  8 years of software engineering experience, including relevant experience in Generative AI.

Strong hands-on experience in  Python  and backend development.

Experience developing  RAG, LLM and AI-agent based applications.

Hands-on experience with  LangChain, LangGraph or equivalent frameworks.

Strong understanding of  vector databases, embeddings and semantic search.

Experience with  Weaviate, Pinecone, Qdrant or similar technologies.

Experience with  OpenAI, Claude, Llama or AWS Bedrock.

Experience with  FastAPI, REST APIs, microservices and scalable backend systems.

Good knowledge of  SQL, PostgreSQL, MongoDB and Redis.

Experience with  AWS, Docker, Kubernetes and CI/CD.

Knowledge of  AI evaluation, prompt engineering, guardrails and security.

Strong analytical, problem-solving and communication skills.

Preferred Experience

Experience in  financial services, investment management, insurance or financial document processing.

Experience in  KYC/AML, compliance or financial document intelligence.

Knowledge of  LangSmith, RAGAS, Arize Phoenix or similar AI evaluation tools.

Experience with  AWS Textract or document extraction technologies.