Key Responsibilities :
- Design and develop enterprise-scale agentic AI solutions using LangGraph and related frameworks
- Build and optimize RAG systems (chunking, retrieval strategies, evaluation) with an emphasis on accuracy, latency, and reliability.
- Architect multi-step reasoning workflows that integrate with existing enterprise systems and APIs
- Collaborate with cross-functional teams to translate business requirements into scalable AI solutions
- Ensure AI implementations meet enterprise security, compliance, and governance standards
- Optimize system performance and cost efficiency across multiple LLM providers
- Mentor junior developers and contribute to AI development best practices
- Partner with DevOps teams to ensure reliable production deployments.
Required Qualifications :
Bachelor's degree in Computer Science, Engineering, or related technical field3-5 years of software development experience with demonstrated expertise in AI / ML technologiesStrong proficiency in Python with experience in asynchronous programming patternsProven track record of implementing production LLM integrations (OpenAI, Anthropic, Azure OpenAI, etc.)Hands-on experience with RAG system development including vector databases, embedding models, and retrieval optimizationKnowledge of enterprise software architecture patterns and API integration best practicesUnderstanding of AI governance, security, and ethical AI principlesStrong understanding of prompt engineering techniques and LLM behavior optimizationPreferred Qualifications :
Experience with agent frameworks (LangChain / LangGraph preferred) and multi-step reasoning implementations.