Forward Deployed Engineer

About the Role

As a Forward Deployed Engineer at Trase, you’ll build and deploy AI agents and applications that solve real customer problems using Trase OS. You’ll join Leagues, our industry verticals team, supporting customers in healthcare, state and local government and education (SLED), financial services, or retail. Your focus may be one or more of these verticals; experience in all four is not required.

This is a hands-on software engineering role with direct customer ownership. You’ll work with users to understand their workflows, turn unclear requirements into technical plans, and take solutions from prototype through production. You’ll partner closely with Product, ML, and the Origin and Arena engineering teams to build on Trase OS and feed customer needs back into the platform.

We are hiring at Mid, Senior and Staff levels. Level will reflect your demonstrated engineering depth, independence, and scope of ownership.

Why This Role is Needed

Customer value depends on how well AI works within existing systems, data, and day-to-day operations. Leagues connects Trase OS to those environments and turns platform capabilities into solutions customers can use and trust.

This role exists to:

Deliver working solutions that improve customer workflows and produce measurable outcomes.

Bridge customer needs and platform engineering, identifying gaps early and shaping practical solutions.

Turn successful deployments into reusable integrations and patterns that help future customers launch faster.

What makes this role challenging

Customer environments vary in data quality, integration options, security requirements, and operational readiness.

AI behavior must be evaluated against real workflows, including failure cases, escalation paths, and human review.

You must balance delivery speed with reliability and maintainability, while deciding what belongs in a customer solution versus the shared platform.

Responsibilities

Work directly with customers to map workflows, identify useful AI applications, and agree on scope, success measures, and acceptance criteria.

Build production-quality agents, applications, APIs, and integrations using Trase OS, including backend services and user interfaces as needed.

Integrate customer systems, data sources, and identity providers; work with infrastructure engineers to deploy in customer or Trase-managed environments.

Own delivery through testing, deployment, customer validation, and operational handoff. Surface dependencies, risks, and scope changes early.

Build evaluations, automated tests, observability, and human review or escalation into agent workflows; validate quality, latency, cost, and reliability.

Apply appropriate access controls, data-handling policies, and audit logging in partnership with Security and customer teams.

Debug production issues across application, data, integration, and infrastructure layers; document solutions and create practical runbooks.

Contribute reusable components and product feedback to Origin and Arena; collaborate on platform improvements rather than maintaining unnecessary custom implementations.

Requirements

Experience building and shipping production software, with strong coding, testing, debugging, and API design fundamentals.

Proficiency in a modern language such as Python, Java or TypeScript, and experience with databases, backend services, and external integrations.

Working knowledge of cloud infrastructure, containers, CI/CD, and monitoring; ability to troubleshoot deployed applications.

Ability to translate customer needs into implementable work and communicate clearly with technical and non-technical stakeholders.

Practical understanding of LLM applications or AI agents, including their limitations, evaluation, and safe interaction with customer data and systems.

Ownership of delivery and quality, curiosity about customer operations, and comfort working through incomplete requirements.

Nice to Have

Experience as a forward deployed, product, full stack, or solutions engineer with substantial production coding responsibility.

Domain experience in healthcare, SLED, financial services, or retail; familiarity with sensitive data and regulated customer environments.

Experience with agent orchestration, retrieval, LLM evaluations, enterprise identity, or complex enterprise integrations.

Expectations by level:

Engineer II (L4): Deliver scoped features and integrations with guidance; contribute to customer discovery, testing, and production troubleshooting.

Senior Engineer (L5): Independently lead a customer workstream from discovery to production, make design decisions, and mentor engineers.

Staff Engineer (L6): Lead complex deployments and architecture across teams, resolve broader technical risks, and establish reusable patterns across Leagues.

If you want to be on the cutting edge of technology, building AI solutions for the future, and are up for a challenge, let’s talk!

Salary Range: $150,000-240,000. This represents the typical salary range for this position based on experience, skills, and other factors.

Some travel to customers may be required.