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.
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Artificial Intelligence Engineer • Shimoga, Karnataka, India
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