- Design and deliver enterprise-grade AI solutions using LLMs and modern AI frameworks
- Build and optimize applications using LangChain, LangGraph, and multi-agent architectures
- Drive end-to-end development lifecycle from problem definition to production deployment
- Collaborate with cross-functional teams to translate business needs into AI solutions
- Develop and deploy LLM-based applications using RAG, embeddings, and prompt engineering
- Build and manage multi-agent systems and workflows using LangGraph, MCP, or similar frameworks
- Design scalable AI pipelines, APIs, and integrations for production use
- Optimize performance, cost, and reliability of AI systems in production
- Collaborate with product, engineering, and data teams to deliver business impact
- 4–6 years of experience in AI/ML engineering or related roles
- Strong Python programming skills (mandatory)
- Experience with LLMs, LangChain, LangGraph, and agent frameworks
- Hands-on knowledge of multi-agent systems and MCP (or similar protocols)
- Understanding of RAG, embeddings, prompt engineering, and LLM orchestration
- Experience in deploying AI solutions on cloud platforms (Azure/AWS/GCP)
- Strong communication skills and ability to work with cross-functional teams
- Experience with MLOps practices, APIs, and production deployments