Forward Deployed Engineer

Why This Role Exists The company is scaling its enterprise motion around its orchestration platform—a programmable agent platform for running and coordinating agents at scale. The platform’s cloud agents are background agents that run from events, schedules, or integrations, giving engineering teams scalable automation with shared observability. Every enterprise has different security requirements, internal tooling, and use cases. The company needs someone to bridge the gap between its platform and customers’ unique environments. As enterprises adopt the orchestration platform, they require hands‑on technical leadership to deploy production agent workflows: architecting solutions, configuring environments, building integrations, guiding self‑hosted deployments, and iterating on prompts and skills until the agents deliver real business value. The company is seeking a Forward Deployed Engineer—the first hire dedicated to making enterprise implementations successful, turning promising pilots into production deployments that drive real results. This role sits at the intersection of engineering, product strategy, and go‑to‑market. The engineer will build alongside customers, not just advise them, and will report to leadership with direct exposure across every part of the business. What the Founding Forward Deployed Engineer Will Do Own end‑to‑end enterprise implementations – Lead engagements from the first discovery call through production deployment. Conduct deep discovery on customer engineering environments, define success criteria, architect agent workflows tailored to their stack, and own the outcome from start to finish. Architect agent workflows with customers – Help enterprise engineering teams design agent architectures for their specific use cases: selecting triggers (Slack, Linear, GitHub Actions, webhooks, cron schedules, API calls), configuring sandboxed environments, structuring multi‑step agent workflows, and designing integration‑driven automation that fits into the customers’ existing development lifecycle. Build production‑grade solutions alongside customers – Write and iterate on agent prompts, skills, and configurations. Set up environments, secrets, MCP servers, and integrations. Debug agent runs using session sharing and observability tools. Ship a working version in days, then harden it over weeks with proper monitoring and iteration based on real usage. Guide self‑hosted deployments – For enterprises that need execution on their own infrastructure, help configure managed workers (Docker, Kubernetes, or a direct backend), set up task routing, connect private registries, and validate network connectivity—ensuring customers receive the same orchestration and observability benefits as platform‑hosted execution. Accelerate deals through technical execution – Join customer calls from the very first discovery meeting to understand technical environments and identify opportunities for cloud agents. Develop reusable implementation patterns – Turn what is built into reusable patterns that make the next implementation faster. Document architecture patterns, reference implementations, agent skills, and templates. Be the voice of the customer to Product and Engineering – Surface implementation friction, feature gaps, and common pain points. Translate field learnings—which integrations should become first‑party, what is blocking faster deployments, where the platform needs to evolve—into actionable feedback that shapes the orchestration platform’s roadmap. Who the Company Is Looking For A strong, customer‑focused engineer – A CS degree or equivalent experience. Candidates will go through the company’s standard software engineering interview loop because the role requires building production‑quality solutions, not just advising on them. Forward Deployed (or equivalent) experience – Ideally, the candidate has most recently worked as a Forward Deployed Engineer, or has been an early engineer or founder at a startup where they worked closely with go‑to‑market teams and did pilot implementations for enterprises. The key signal: they have built custom technical solutions for customers, not just internal products. Strong infrastructure fundamentals – Comfortable with Docker, CI/CD pipelines, cloud infrastructure (AWS, GCP, Azure), container orchestration, and Linux. Understands how enterprise engineering environments work and can navigate them confidently. Familiarity with AI / LLM concepts – Understands prompt engineering, agent architectures, tool use, and how to evaluate non‑deterministic systems. Has built or deployed AI‑powered workflows in production—not just prototypes, but systems that run in production. Excellent communication skills – Can hold their own with senior engineers and executives alike. Needs to articulate the company’s vision for its orchestration platform in a way that gets enterprise engineering teams and leadership excited. High EQ and the ability to navigate enterprise relationships – Working with other companies’ engineers requires a different approach than internal collaboration. The ideal candidate knows how to be amenable, patient, and constructive even when things are not set up the way they would prefer. Bonus Qualifications Experience building or deploying AI agents in production (LangChain, custom agent frameworks, or similar) Experience with GitHub Actions, webhooks, and event‑driven automation Familiarity with enterprise security and compliance requirements (SOC 2, self‑hosted deployments, network boundary constraints) Experience with APIs/SDKs in a customer‑facing capacity (building integrations, writing client libraries, or doing technical enablement) Experience with terminal applications, shell scripting, or command‑line tooling Experience with Python, Node, Rust or Go Show more Show less