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Salary: USD 140,000 - 200,000 / annual
Standard Template Labs is an AI-native seed-stage startup transforming enterprise IT Service and Configuration Management. The company leverages AI, graph-based architecture, and design to help enterprises turn historical ticket data, knowledge bases, and integrations into instant resolutions and automated workflows.
As a Forward Deployed Engineer, you'll be embedded in customer environments—their data, integrations, and constraints—making the platform real in production. This role sits at the intersection of engineering and customer success, requiring someone who thrives in the room where problems actually exist.
Key responsibilities include deploying the platform inside enterprise environments (potentially on-site), incrementing on production code (integrations, data pipelines, agent workflows, internal tooling), wiring the platform into existing customer systems (ticketing, identity, device management, knowledge bases), owning live deployments from day one, and feeding learnings back into the product. You'll see more of how enterprises actually run service operations than anyone else at the company.
Required qualifications: 2–3 years writing software professionally, or a strong engineering degree plus an internship where you shipped something real. Comfortable in Python and TypeScript (or confident you can be by month two). Experience integrating against third-party APIs and working with messy, undocumented production data. A track record of building things outside assigned work (tools, apps, open-source contributions). Desire to be in front of customers, not just tolerate it. Ability to stay when work gets unglamorous with a specific example.
Bonus qualifications include hands-on LLM work (agents, tool use, retrieval, evals—shipped, not demoed), exposure to ITSM/CMDB/enterprise IT operations, or two years in technical consulting/solutions engineering with a strong urge to write more code.
The role offers real problems with real impact, high ownership with low process, technical depth (graph databases, LLM orchestration, self-healing integrations, natural language workflow engines deployed in real enterprise environments), competitive compensation and equity, and an on-site collaborative workspace in Midtown Manhattan five days a week with the founding team, plus potential travel to customer sites.
