Forward Deployed Engineer

Co-founded in 2023 by Joe Laws and Grant Verstandig, Trase Systems is AI, Uncomplicated. Trase empowers enterprise leaders to harness the full potential of AI without the associated complexity and risks. We are an end-to-end solution for deploying, managing, and optimizing AI in the enterprise. Our platform specializes in bridging the “last mile” of AI adoption, unlocking AI's full potential while driving efficiency and significant cost savings. Trase is at the forefront of AI Agent innovation, topping the Hugging Face GAIA Leaderboard for Generalized AI Assistants, ahead of industry giants such as Google, Meta, Microsoft, and OpenAI. We are leveraging our cutting-edge technologies to develop mission-critical agentic applications in complex industries such as Healthcare, Oil & Gas, and National Security. 

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.

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.

• 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.

• 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.

• →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.

• 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.

• 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.

• 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!