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TT

JR AI Agentic Developer

Ttsiglobal
Posted 4 hours ago
🇺🇸United States🏠Remote📁Engineering & Development
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Professional Summary Junior developer (0–3 years) with hands-on experience designing and shipping agentic AI systems. Fluent with AI-assisted development tooling (Cursor, Claude Code) and 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 - with the judgment to know when an agent is the right architecture and when a deterministic workflow is. Startup experience and supply chain or ERP domain exposure are significant differentiators. Core Skills (Required) • Agentic Frameworks: LangChain / LangGraph (state graphs, checkpointing, conditional edges, human-in-the-loop) or CrewAI (role-based crews, task delegation, sequential and hierarchical processes) • Agentic AI Concepts: ReAct, plan-and-execute, reflection, tool calling and schema design, memory management, context-window strategy, guardrails, and agent evaluation • AI Development Tooling: Cursor, Claude Code, MCP servers, prompt iteration and debugging • API Development: FastAPI - async endpoints, Pydantic models, dependency injection, SSE/streaming responses, background tasks; used to expose agent workflows as production services • Programming: Python (async/await, typing, pytest), Git, Docker • Location: open to candidates anywhere in the United States; remote, hybrid, or onsite. Must be authorized to work in the U.S. Preferred Skills • n8n: workflow orchestration, webhook triggers, scheduled runs, integrating agents with external systems and business tooling • RAG: chunking strategies, embeddings, hybrid (semantic + keyword) search, re-ranking, citation grounding, retrieval evaluation • Vector Databases: pgvector, Pinecone, Qdrant, Weaviate, or Chroma • Graph Databases: Neo4j and Cypher; GraphRAG and knowledge-graph-backed retrieval • Kubernetes: containerization, Helm charts, deploying and scaling agent services on a cluster • Startup Experience: 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 • Supply Chain Domain: exposure to supply chain, procurement, logistics, or ERP systems (Oracle, SAP, NetSuite) - understanding of purchase orders, suppliers, inventory, demand planning, and fulfillment workflows Trillion is an equal opportunity employer. Applicants are considered for positions without regard to race, religion, gender, native origin, age, disability, or any other category protected by applicable federal, state, or local law.

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