Forward Deployment Engineer

Job Description

Forward Deployment Engineer - Agentic AI Infrastructure
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Fully Remote with client site travel
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I'm partnering with an early-stage AI infrastructure company building a runtime control plane for the agentic enterprise technology designed to help organizations safely deploy, monitor, govern, and scale autonomous AI agents in production.
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They're building at the intersection of AI infrastructure, observability, security, and enterprise deployment, giving organizations visibility and control over increasingly complex ecosystems of AI agents.
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They're now looking for a Forward Deployment Engineer to join their small, senior engineering team and become one of the first technical people customers work with.
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This is a highly hands-on role combining software engineering, AI infrastructure, and customer-facing technical delivery. You'll embed directly with enterprise engineering, platform, and security teams, own deployments end-to-end, and feed what you learn in the field directly back into the product.
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Day to day:
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Lead enterprise deployments from initial integration through production
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Build integrations and adapters across agent frameworks, model providers, and observability stacks
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Configure policies, evaluators, and dashboards for customer environments
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Troubleshoot complex production issues across AI and enterprise infrastructure
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Turn customer requirements and field learnings into product improvements
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Work closely with the founders, Product, and Engineering to influence the roadmap
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Contribute directly to production code
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Skillset:
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2+ years of software engineering experience with customer-facing technical exposure
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Strong Python and TypeScript
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Experience with Kubernetes and Docker, particularly in secure/on-prem environments
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Exposure to LLMs, GenAI systems, or agent frameworks
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Comfortable operating in ambiguous, fast-moving startup environments
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Strong communication skills and the ability to work directly with enterprise customers
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Experience with LangChain, LangGraph, MCP, AI/ML infrastructure, observability, developer tooling, enterprise security, or engineering consulting would be particularly relevant.
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This is a great opportunity for someone who wants more than a traditional software engineering role. You'll have direct customer exposure, meaningful product influence, significant technical ownership, and the chance to help define how enterprise AI agents are deployed and governed in production.