CoffeeBeans
Coffeebeans.io - AI Engineer - Deep Agent Architectures
Skills
8 days ago
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Important information
Contract type:
Permanent
Location:
Odisha, India
Work mode:
Onsite
Published on:
17 October 2026
What they need
Technical Skills & Requirements AI Agents & Deep Agent Architectures :
- Frameworks : Expert-level mastery of LangGraph for building complex, cyclic, and stateful agentic workflows.
- Deep Agents Harness : Hands-on experience implementing the Deep Agents open-source library built on top of LangGraph, leveraging its native architectural patterns.
- Advanced Reasoning Patterns : Proven experience building agents with built-in dynamic task planning (to-do lists), isolated sub-agent spawning, and persistent virtual file systems within the graph state.
- State Management & Interruption : Mastery over LangGraph state machines, including context compression middleware and the use of interrupt nodes to manage asynchronous human-in-the-loop (HITL) approval checkpoints.
LLMOps, Evaluation & Guardrails
- Evaluation Frameworks : Extensive experience with Ragas (Retrieval Augmented Generation Assessment) to programmatically benchmark faithfulness, context recall, and answer relevance.
- Guardrails & Alignment : Implementation of strict security and behavior firewalls using frameworks like NeMo Guardrails, Guardrails AI, or Llama Guard.
- LLM Telemetry : Experience mapping evaluation metrics into observability tools such as LangSmith, Phoenix, TruLens, or Arize.
Advanced Retrieval (RAG) & Tool Integration
- Vector Ecosystems : Experience with vector databases (e.g., Pinecone, Chroma, Milvus, Qdrant) and advanced retrieval techniques (hybrid search, cross-encoder re-ranking).
- Deterministic Tool Calling : Expert-level Python or TypeScript proficiency to build robust agent function-calling mechanisms, integrating seamlessly with enterprise REST APIs, webhooks, and SQL/NoSQL databases.
Production Deployment & Monitoring
- Infrastructure : Deep understanding of containerized deployment (Docker, Kubernetes) within enterprise cloud environments (AWS, Azure, or GCP).
- Auditability : Experience setting up structured logging and immutable telemetry pipelines (Datadog, Prometheus, ELK stack) for complete audit trails.
(ref:hirist.tech)
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