ML/AIWork

Forward Deployed Engineer

Middesk · New York, US

Job description

About Middesk:

Middesk makes it easier for businesses to work together. Since 2018, we’ve been transforming business identity verification, replacing slow, manual processes with seamless access to complete, up-to-date data. Our platform helps companies across industries confidently verify business identities, onboard customers faster, and reduce risk at every stage of the customer lifecycle.

Middesk came out of Y Combinator, is backed by Sequoia Capital and Accel Partners, and was recently named to Forbes Fintech 50 List.

About the Role:

We're hiring a Forward Deployed Engineer (FDE): a deeply technical builder and technical leader who thrives at the intersection of engineering, product, and real customer problems.

You'll work shoulder-to-shoulder with customers and internal product and engineering teams to design, ship, and iterate on mission-critical integrations and AI-driven systems that run in production. You'll write real code, own complex deployments end-to-end, and help shape how these systems are built across Middesk. Forward Deployed Engineers close the gap between product intent and real-world usage—acting as a tight feedback loop that shapes both how our product is used and what it becomes.

You will act as a technical leader, helping set direction, influence architecture, and establish best practices for how we deploy and operate systems in the real world.

This role is ideal for a recovering founder, a former core engineer who misses direct customer impact, or someone who thrives on ownership and wants to build real systems where the feedback loop is immediate.

What You’ll Do:

Own Technical Direction for Deployments

  • Lead architecture and technical design for complex, customer-facing systems and integrations.
  • Make and communicate clear trade-offs across speed, reliability, and scalability.
  • Identify systemic risks and drive improvements across deployments, not just one-off solutions.
  • Establish patterns and standards that other engineers can build on—helping define what "great" looks like for Forward Deployed Engineering at Middesk.

Build & Deploy Real Systems

  • Partner deeply with strategic customers to understand their architecture, workflows, and constraints.
  • Design, build, and deploy production-grade integrations using Middesk APIs, data pipelines, and AI workflows.
  • Own deployments end-to-end: from architecture and implementation to rollout, monitoring, and iteration. Deployment quality matters—we operate in the critical path of customer systems.
  • Solve ambiguous, high-impact problems that don't yet have established playbooks.

AI, Agents & Evaluation

  • Build and operate LLM- and agent-based systems in real customer workflows.
  • Design and maintain evaluation frameworks (evals) to measure quality, reliability, and correctness of LLM outputs and agent behavior.
  • Create test harnesses, metrics, and feedback loops to continuously improve AI-driven systems.
  • Feel comfortable running multiple coding agents or automated workflows in parallel, debugging failures, and reasoning about system behavior.

Influence Product & Engineering Direction

  • Translate deployment learnings into reusable abstractions, internal tooling, and product improvements.
  • Influence roadmap priorities by surfacing recurring patterns, technical gaps, and opportunities for leverage.
  • Participate in architecture discussions and contribute to org-wide technical decisions.
  • We believe engineering velocity is only valuable if it delivers customer value—your role is to make sure it does.

Lead & Raise the Bar

  • Lead through influence, not authority—setting a high standard for engineering quality and pragmatism in a high-ownership, high-trust environment.
  • Guide engineers through design reviews, code reviews, and hands-on collaboration.
  • Enjoy real autonomy, direct influence on product direction, and deep technical problems with real-world impact.
  • Work with a team that values thoughtful engineering over performative process.

What We’re Looking For:

Core Requirements

  • 6+ years of experience building and shipping software in production environments.
  • Demonstrated experience acting as a technical lead or domain owner for a team or major system.
  • Strong proficiency in Python and at least one additional language (TypeScript, Go, etc.).
  • Experience designing and operating distributed systems, APIs, and cloud-native infrastructure.
  • Comfort operating across the stack: backend systems, integrations, infrastructure, and tooling.
  • Strong debugging instincts and an ownership mindset—you care deeply about failure modes, not just happy paths.
  • Strong communication skills—able to articulate trade-offs clearly to engineers, product, and non-technical stakeholders.

AI / LLM Experience (Strong Plus)

  • Hands-on experience building or deploying LLM-powered or agent-based systems.
  • Familiarity with LLM evaluation techniques (evals) and performance measurement.
  • Experience orchestrating automated workflows, agents, or developer tooling powered by AI.
  • Clear understanding of failure modes and tradeoffs in applied AI systems.

Customer & Domain Experience

  • Experience working in startup environments with high ambiguity and rapid iteration.
  • Background in fintech, compliance, or regulated systems where correctness and data quality matter.
  • Comfortable working directly with customers on complex technical problems.

Nice-To-Have:

  • Former founder or early startup engineer.
  • Experience with identity systems, risk/fraud, or workflow automation.
  • Familiarity with observability, reliability engineering, or system safety practices.

Compensation Range: $148K - $275K

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