Job Title

Associate / Staff GenAI Engineer

Role Overview

We are looking for a GenAI Engineer (3+ years’ experience) who can build, integrate, and maintain GenAI components under defined architectures. The role focuses on implementation, optimization, and delivery of GenAI solutions while working closely with senior engineers and managers.

Key Responsibilities

• Implement RAG pipelines based on provided architecture and design guidelines
• Develop and optimize prompts under defined standards and review processes
• Build API services using FastAPI and integrate GenAI capabilities into applications
• Implement agent workflows using LangChain and LangGraph as per solution design
• Integrate vector databases and tune embeddings for retrieval accuracy
• Consume LLMs from AWS Bedrock and Azure OpenAI following best practices
• Implement JWT authentication for secure API access
• Develop and deploy services on AWS, following existing CI/CD and infra standards
• Add logging and basic monitoring to GenAI pipelines
• Participate in code reviews, testing, and documentation
• Collaborate with senior engineers and managers on delivery and improvements

Mandatory Skills

• 3+ years of experience in Python-based development
• Strong Python Object-Oriented Programming skills
• Working knowledge of GenAI concepts: RAG, chunking, CoT, guardrails
• Experience in Prompt Engineering and prompt iteration
• Hands-on experience with LangChain and/or LangGraph
• Strong FastAPI and REST API integration experience
• Basic to intermediate AWS knowledge, including DynamoDB
• Experience implementing JWT authentication in Python
• Working knowledge of vector databases and embeddings
• Familiarity with AWS Bedrock and Azure OpenAI

Good to Have

• Basic understanding of LLMOps / MLOps concepts
• Exposure to logging, monitoring, and evaluation signals for GenAI systems
• Experience working on enterprise chatbots or GenAI-backed applications

What we are looking for

• Strong execution mindset and willingness to learn
• Ability to work within defined architectures and coding standards
• Clear understanding of boundaries between delivery and design ownership
• Good communication and collaboration skills
• Focus on quality, performance, and reliability