Senior Software Engineer - Python

We are seeking an experienced AI Engineer to design and build production-grade Generative AI solutions with a strong focus on agentic workflows, multi-agent systems, and enterprise AI applications. The ideal candidate combines strong software engineering fundamentals with handson expertise in LLMs, RAG architectures, and AI agent frameworks.

Responsibilities

Design, architect, and develop scalable Generative AI applications and agentic solutions for real-world business use cases

Build and orchestrate AI agents using frameworks such as LangChain, LangGraph, Google ADK, CrewAI, AutoGen, Microsoft Copilot Studio, or similar technologies

Develop and maintain backend services, APIs, microservices, and data pipelines that power AI-driven products

Implement advanced AI patterns including RAG, Agentic RAG, tool/function calling, planning & reflection loops, and human-in-the-loop workflows

Engineer and 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, evaluate, and continuously improve model and agent performance using observability tools, metrics, and user feedback

Collaborate closely with Product, Engineering, Data, and Design teams to deliver impactful AI solutions

Stay current with emerging AI technologies, frameworks, and best practices, contributing innovative ideas to the team

Document architectures, design decisions, and reusable solution patterns while supporting knowledge sharing across teams

Requirements

5-7 years of experience in software engineering

Handson experience building applications using Generative AI and LLM technologies

Strong proficiency in Python and experience developing productionready applications

Handson experience with at least two agentic AI frameworks such as LangChain, LangGraph, Google ADK, CrewAI, AutoGen, or Microsoft Copilot extensibility

Experience with cloud AI platforms including Azure OpenAI, AWS Bedrock, or Google Vertex AI/ADK

Strong backend development skills, including REST/gRPC APIs, asynchronous programming, Docker, and frameworks such as FastAPI or Flask

Solid understanding of leading LLMs including OpenAI GPT models, Anthropic Claude, Google Gemini, and open-source alternatives

Practical experience building RAG solutions using vector databases such as Pinecone, Weaviate, ChromaDB, or Qdrant

Expertise in prompt engineering, LLM orchestration, structured outputs, guardrails, ReAct patterns, and evaluation techniques

Strong problemsolving, system design, and architectural decisionmaking skills

Excellent communication skills with the ability to collaborate effectively across global teams .