Lead Software Engineer (Python, GenAI, LLM)

Role overview

Responsibilities

• Design, architect, and develop scalable Generative AI applications and agentic solutions for real-world business use cases.
• Build and orchestrate AI agents with frameworks such as LangChain, LangGraph, Google ADK, CrewAI, AutoGen, or Microsoft Copilot Studio.
• Develop backend services, APIs, microservices, and data pipelines that power AI-driven products.
• Implement RAG, Agentic RAG, tool and function calling, planning and reflection loops, and human-in-the-loop workflows.
• Optimize prompts, system instructions, and agent workflows to improve reliability, accuracy, and user experience.
• Integrate LLMs with enterprise systems, third-party APIs, vector databases, and knowledge repositories.
• Monitor and improve model and agent performance using observability tools, metrics, and user feedback.
• Collaborate with Product, Engineering, Data, and Design teams to deliver AI solutions.
• Document architectures, design decisions, and reusable solution patterns while supporting knowledge sharing.

Requirements

• 7 to 12 years of relevant professional experience.
• Hands-on experience building applications using Generative AI and LLM technologies.
• Strong Python proficiency and experience developing production-ready applications.
• Experience with at least two agentic AI frameworks, such as LangChain, LangGraph, Google ADK, CrewAI, AutoGen, or Microsoft Copilot extensibility.
• Experience with Azure OpenAI, AWS Bedrock, or Google Vertex AI/ADK.
• Backend experience with REST or gRPC APIs, asynchronous programming, Docker, and FastAPI or Flask.
• Experience with leading LLMs, RAG solutions, vector databases, prompt engineering, orchestration, guardrails, and evaluation techniques.
• Strong problem-solving, system design, architectural decision-making, communication, and collaboration skills.