Description

Responsibilities

• Design, build, and deploy AI agents into production environments serving real users.
• Develop and orchestrate multi-agent workflows, tool integrations, and autonomous decision-making frameworks.
• Develop, test, and optimize AI-driven applications that leverage large language models, agent frameworks, and retrieval capabilities.
• Design and implement RAG (Retrieval-Augmented Generation) architectures using vector databases.
• Implement agentic workflow patterns including tool calling, ReAct frameworks, and Human-in-the-Loop workflows.
• Troubleshoot, monitor, and support AI-enabled applications in production environments.
• Optimize latency, throughput, and inference costs for LLM applications.
• Implement guardrails and responsible AI practices to reduce hallucinations and unsafe outputs.
• Collaborate on enterprise architecture, scalability, reliability, and observability requirements.

Qualifications

• Required
  • Strong proficiency in both Python and Java, with hands-on experience developing and supporting production-grade applications.
  • Demonstrated experience building, deploying, and maintaining Agentic AI solutions in enterprise environments.
  • Experience designing and orchestrating multi-agent workflows, tool integrations, and autonomous decision-making frameworks.
  • Hands-on experience with LangChain and/or LangGraph.
  • Experience with tool calling, ReAct frameworks, and Human-in-the-Loop (HITL) workflows.
  • Experience designing and implementing RAG architectures and working with vector databases such as Pinecone, Milvus, or Weaviate.
  • Experience with vLLM and LLM deployment/inference frameworks.
  • Strong understanding of API development, microservices architectures, and integration patterns within modern software ecosystems.
  • Ability to design, build, and deploy AI agents to production serving real users, with demonstrable business outcomes and adoption metrics.
  • Understanding of scalability, reliability, observability, and enterprise architecture.
  • Familiarity with responsible AI practices, model governance, security considerations, and enterprise development standards

Key Skills

Education

Not specified