The Role
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.
What You'll Do
- 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
What You Bring
- 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
Nice to Have
- Familiarity with MLOps tools (MLflow, Weights & Biases, SageMaker, or similar)
- Exposure to cybersecurity or GRC tooling (Vanta, OneTrust, ServiceNow GRC, or similar)
- Experience in legaltech, cybersecurity, or another regulated/compliance-driven market
- Prior experience at an early or growth-stage startup
Compensation & Benefits
- Base salary: $125,000 - $145,000, commensurate with experience
- Meaningful equity in an early-stage, venture-backed company
- Health, dental, and vision coverage
- Unlimited PTO
