Solutions Engineer, AI Governance Enablement

AI is reshaping every industry on earth, and right now, almost no one has figured out how to govern it. Trustible exists to meet that challenge. We're building the platform that lets the world's largest organizations move fast with AI and prove they're doing it responsibly.

We're an AI-native Public Benefit Corporation headquartered in Arlington, Virginia, backed by over $6M in venture funding from investors betting on trustworthy AI as one of the defining infrastructure categories of the decade. We're winning enterprise customers in some of the most impactful industries in the world, and this role sits right at the point where our platform meets their reality.

We're hiring a Solutions Engineer to be the technical face of Trustible for our customers. You'll lead data migrations, configure the platform for each customer's environment, and build integrations with the tools they already use. This is hands-on technical work: you'll be in the data, in the config, and sometimes in the code, solving real problems for real organizations trying to get AI governance right.

We call this AI governance enablement because the job is bigger than "get the platform running." You're helping each customer's rollout reflect how their organization actually governs AI, so the platform earns trust and becomes something teams rely on rather than another item to check off.

• Lead customer data migrations into Trustible, including mapping, transformation, and validation
• Configure the platform to match each customer's governance structure, workflows, and permissions model
• Build and maintain integrations between Trustible and customer tools (ML platforms, ticketing systems, identity providers, and similar)
• Troubleshoot technical issues during onboarding and beyond, partnering closely with engineering on the trickiest ones
• Work with customer teams to understand their AI governance program and translate that into platform configuration
• Contribute to internal tooling and scripts that make onboarding faster and more repeatable
• Document integration patterns and configuration playbooks so the team can scale without reinventing the work each time

• 3-5 years of experience in a technical, customer-facing role: solutions engineering, implementation, technical account management, or similar
• Strong SQL skills and comfort working directly with customer data during migration and transformation
• Experience with API integrations and enough backend fluency to troubleshoot issues confidently and know when to bring in engineering
• Excellent communication skills. You move easily between explaining a technical constraint to a business stakeholder and working through details with a customer's engineering team
• Real curiosity about AI governance, risk, or compliance, and an eagerness to build expertise in the space
• Comfort with ambiguity. Every customer's environment and requirements look a little different, and you enjoy figuring out the right approach each time

• Familiarity with MLOps tools (MLflow, Weights & Biases, Sage Maker, or similar)
• Exposure to cybersecurity or GRC tooling (Vanta, One Trust, Service Now GRC, or similar)
• Experience in legaltech, cybersecurity, or another regulated/compliance-driven market
• Prior experience at an early or growth-stage startup
• Base salary: $125,000 - $145,000, commensurate with experience
• Meaningful equity in an early-stage, venture-backed company