Description

Key Skills: Agentic AI, AWS, LangGraph, AutoGen Framework, Debugging, Redis, Pinecone, Kubernetes, Datadog

Roles & Responsibilities:

• Design and deliver production-grade Agentic AI and Generative AI systems.
• Architect agentic AI solutions including planning, reasoning, tool-calling, and RAG pipelines.
• Prepare technical design documents, flow diagrams, UML/sequence diagrams, and AWS deployment architectures.
• Optimize systems for performance, cost, latency, throughput, concurrency, and scalability.
• Troubleshoot complex technical issues, resolve critical defects, and handle production incidents.
• Develop and standardize agentic AI solutions using LangGraph, AutoGen, Semantic Kernel, or CrewAI.
• Implement monitoring and observability using OpenTelemetry and Datadog.
• Build testing and evaluation frameworks, including regression testing and A/B experiments.
• Develop reusable SDKs, connectors, and CI/CD standards.
• Support capacity planning, disaster recovery, and incident reviews.
• Mentor engineers and improve system design and reliability practices.

Experience Required:

• 7-10 years of experience in software engineering, AI/ML, or related technologies.
• Strong experience in Agentic AI, Generative AI, and RAG solutions.
• Hands-on experience with AWS, LangGraph, and AutoGen Framework.
• Experience with Redis, Pinecone, Kubernetes, and Datadog.
• Strong debugging, troubleshooting, and production incident management skills.
• Experience designing scalable and high-performance AI systems.
• Good understanding of observability, monitoring, testing, and CI/CD practices.

Education: Master's, M.E., B.Tech/M.Tech (Dual), B.E., or B.Tech

Key Skills

Education

Any Graduate