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Remote role, popular AI title, and mid-level experience drive high competition.
Skills are transferable across industries but require specific LLM/agent and orchestration experience.
Explicit 3+ years plus mandatory agent, LangChain/LangGraph, and deployment skills make filters strict.
Design, implement, and deploy multi-step AI agents and orchestration workflows mainly using Python and AI platforms like LangGraph, LangChain, AWS Bedrock.
Integrate and evaluate top AI models (e.g., Gemini, GPT, Claude) and connect agents to real systems via APIs, SaaS apps, webhooks, and events.
Own full production lifecycle from prototype to deployment including CI/CD, containers, cloud deployment, instrumentation, and client collaboration to deliver measurable business value.
3+ years of hands-on experience building and shipping AI agents or complex automations.
Strong Python skills including asynchronous programming, testing, and packaging.
Experience with AI orchestration tools such as LangGraph or LangChain and platforms like AWS Bedrock, n8n, Airflow, Prefect, or Temporal.
Software engineering fundamentals with Git, CI/CD pipelines, Docker, and cloud infrastructure (AWS).
Experienced in production-grade AI system development, not research-focused roles, with a strong bias towards delivery speed and quality.
Comfortable owning outcomes end-to-end from design to deployment and client interaction in fast-moving, iterative environments.
Solid foundation in data techniques for embeddings, retrieval-augmented generation, and indexing supporting reliable agent behavior.