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Agent Orchestration Engineer
Key Responsibilities
- Agentic Architecture Design: Develop multi-agent workflows using patterns like Sequential, Parallel, and Manager-Worker to solve complex enterprise problems.
- Orchestration Framework Implementation: Build and maintain agent logic using frameworks such as LangGraph, CrewAI, AutoGen, or Semantic Kernel.
- System Integration: Connect AI agents to enterprise systems (SAP, Salesforce, EHRs) via robust tool-calling and API integrations.
- Memory & Context Management: Design persistent memory layers so agents can remember user preferences and past interactions across long sessions.
- Behavioral Guardrails: Implement safety protocols (e.g., NeMo Guardrails) to ensure agents operate within legal, ethical, and operational boundaries.
- State Machine Management: Handle "Human-in-the-loop" (HITL) checkpoints for high-risk autonomous actions (e.g., approving a $100k loan).
- Performance Monitoring: Use observability tools like LangSmith or Arize Phoenix to debug agent "hallucinations" and optimize token consumption.
Required Technical Skills
- Languages: Advanced proficiency in Python (asyncio, Pydantic) and experience with TypeScript/Node.js.
- Frameworks: Hands-on experience with LangChain/LangGraph, CrewAI, or Microsoft AutoGen.
- Models: Deep understanding of LLM reasoning capabilities (GPT-4o, Claude 3.5 Sonnet, Llama 3) and how to leverage Function Calling and Structured Outputs.
- Data & Memory: Experience with Vector Databases (Pinecone, Weaviate, Milvus) and Graph Databases for knowledge retrieval.
- Deployment: Familiarity with containerization (Docker/K8s) and cloud-native AI services (AWS Bedrock Agents, Azure AI Studio).
Why Join
Saints and Masters?
Join us to innovate, grow, and transform the future of cloud and digital solutions.
- Where Innovation Meets Opportunity
- Be Part of Something Bigger
- Collaborate, Innovate, Excel
- Work-Life Harmony That Works