JR AI Agentic Developer
About The Position
We are seeking a Junior developer with 0-3 years of experience who has hands-on experience designing and shipping agentic AI systems. The ideal candidate is fluent with AI-assisted development tooling (Cursor, Claude Code) and comfortable building production Python services. A strong command of core agentic concepts such as ReAct loops, plan-and-execute, orchestrator-worker patterns, tool/function calling, short- and long-term memory, and multi-agent handoffs is required. The candidate should also possess the judgment to determine when an agent is the right architecture versus a deterministic workflow. Startup experience and exposure to supply chain or ERP domains are considered significant differentiators.
Requirements
- 0-3 years of experience as a developer.
- Hands-on experience designing and shipping agentic AI systems.
- Fluency with AI-assisted development tooling (Cursor, Claude Code).
- Comfortable building production Python services.
- Strong command of core agentic concepts: ReAct loops, plan-and-execute, orchestrator-worker patterns, tool/function calling, short- and long-term memory, and multi-agent handoffs.
- Judgment to know when an agent is the right architecture and when a deterministic workflow is appropriate.
- Experience with Agentic Frameworks: LangChain / LangGraph (state graphs, checkpointing, conditional edges, human-in-the-loop) or CrewAI (role-based crews, task delegation, sequential and hierarchical processes).
- Knowledge of Agentic AI Concepts: ReAct, plan-and-execute, reflection, tool calling and schema design, memory management, context-window strategy, guardrails, and agent evaluation.
- Proficiency with AI Development Tooling: Cursor, Claude Code, MCP servers, prompt iteration and debugging.
- Experience with API Development: FastAPI (async endpoints, Pydantic models, dependency injection, SSE/streaming responses, background tasks).
- Programming Skills: Python (async/await, typing, pytest), Git, Docker.
- Must be authorized to work in the U.S.
Nice To Haves
- Startup experience.
- Supply chain or ERP domain exposure.
- Experience with n8n for workflow orchestration, webhook triggers, scheduled runs, and integrating agents with external systems and business tooling.
- Experience with RAG: chunking strategies, embeddings, hybrid (semantic + keyword) search, re-ranking, citation grounding, retrieval evaluation.
- Experience with Vector Databases: pgvector, Pinecone, Qdrant, Weaviate, or Chroma.
- Experience with Graph Databases: Neo4j and Cypher; GraphRAG and knowledge-graph-backed retrieval.
- Experience with Kubernetes: containerization, Helm charts, deploying and scaling agent services on a cluster.
- Early-stage or small-team background - comfortable with ambiguity, owning a feature end to end, moving from prototype to production quickly, and wearing multiple hats without waiting for process.
- Exposure to supply chain, procurement, logistics, or ERP systems (Oracle, SAP, NetSuite) - understanding of purchase orders, suppliers, inventory, demand planning, and fulfillment workflows.
Responsibilities
- Design and ship agentic AI systems.
- Build production Python services.
- Implement core agentic concepts including ReAct loops, plan-and-execute, orchestrator-worker patterns, tool/function calling, short- and long-term memory, and multi-agent handoffs.
- Expose agent workflows as production services using FastAPI.
- Develop and debug agentic AI systems using AI-assisted development tooling.
Benefits
- Equal opportunity employer.
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
Education Level
No Education Listed
