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 field
• 3-5 years of software development experience with demonstrated expertise in AI/ML technologies
• Strong proficiency in Python with experience in asynchronous programming patterns
• Proven 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 optimization
• Knowledge of enterprise software architecture patterns and API integration best practices
• Understanding of AI governance, security, and ethical AI principles
• Strong understanding of prompt engineering techniques and LLM behavior optimization
Preferred Qualifications:
• Experience with agent frameworks (LangChain/LangGraph preferred) and multi-step reasoning implementations.