Senior AI Engineer Generative AI and Agentic Systems

Skills

About the Role

You will design, build, evaluate, and deploy production-grade Generative AI and agentic AI solutions. You will develop LLM applications and retrieval architectures, integrate them with enterprise systems, establish delivery and monitoring practices, address risks, and mentor junior developers.

Requirements

• Bachelor's degree in Computer Science, Information Technology, Engineering, or equivalent education and experience
• 5–8 years of software development experience, including at least 2 years building production Generative AI or agentic AI applications
• Experience with LangChain, LangGraph, and LLM APIs
• Knowledge of RAG architectures, prompt engineering, and vector databases
• Python proficiency
• Working knowledge of C#, JavaScript, and SQL
• Experience with AWS Lambda, Amazon DynamoDB, Azure, and REST API integration
• Experience with Git, GitHub Actions, Jenkins, and Splunk
• Knowledge of Agile, Lean, and ITIL methodologies

Responsibilities

• Design and develop LLM-powered applications, RAG pipelines, agentic workflows, and autonomous agents
• Build and optimize vector-database retrieval architectures and semantic search
• Apply prompt engineering to improve accuracy, reliability, and cost efficiency
• Serve as a technical contact for AI solution design, feasibility, and delivery timelines
• Integrate GenAI solutions with enterprise systems through REST APIs, webhooks, AWS Lambda, and Azure
• Modernize RPA and automation assets with AI-driven decisioning and self-healing capabilities
• Coordinate AI solution documentation, reviews, and delivery
• Establish CI/CD and monitoring practices with Git, GitHub Actions, Jenkins, and Splunk
• Identify and mitigate model-performance, data-quality, and security risks
• Mentor junior developers on GenAI practices

Hiring Process

Four interview rounds.