Role & responsibilities
- Develop and implement agentic AI systems including tool-calling, autonomous task planning and execution, multi-step reasoning workflows, agent memory management, and human-in-the-loop escalation mechanisms for complex enterprise use cases. Leverage Agentic frameworks like LangGraph, CrewAI, Autogen, cloud-based frameworks, etc.
- Develop and deploy agentic AI solutions using any of the cloud-native services as per defined requirement (Azure AI Foundry, AWS Bedrock Agents, GCP Vertex AI Agent Builder, etc.), and associated cloud services for scalable agent execution.
- Implement and maintain evaluation frameworks for agentic AI solutions assessing agent reasoning, tool-use reliability, multi-step task completion, hallucination risk, and autonomous decision quality to ensure production readiness and continuous performance improvement.
- Design, develop, and optimize RAG pipelines end-to-end (using LangChain, LlamaIndex, etc.) including chunking strategies, embedding model selection, integrate production-grade vector databases (Pinecone, Weaviate, OpenSearch, Azure AI Search, etc.), hybrid retrieval, re-ranking.
- Design, develop, and optimize prompt engineering strategies, including prompt chaining, few-shot/zero-shot techniques, and prompt templating, to enhance the accuracy, reliability, and consistency of LLM-powered applications and agentic workflows.
- Collaborate with cross-functional teams (client managers, data scientists, architects, DevOps engineers) to translate business requirements into technical implementations ? ensuring alignment with solution architecture defined by the lead architects.
- Implement and uphold Python development best practices during implementation.
- Monitor solution performance, track key metrics, test all affected scenarios and proactively adjust implementations ? identifying issues in accuracy, latency, throughput, and cost, and applying optimizations at the code and infrastructure level.
- Communicate technical findings, implementation progress, and insights to stakeholders ? contributing to documentation, sprint demos, and knowledge-sharing within the team
Preferred candidate profile
- Bachelor's Degree
- 4 years of experience