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 .