Senior Engineering Manager, AI Quality & Governance

Mitratech’s AI mission is to turn its legal data and products into a unified, safe AI platform that powers the top legal workflows in every core solution and drives meaningful gains in legal team productivity and AI-influenced revenue.

The mandate is not just to ship isolated AI features. The AI organization owns the platform, standards, and integration patterns that make it possible for product teams to ship safe, impactful AI that improves customer outcomes. The organization is designed using Team Topologies: stream-aligned product teams sit at the top, an AI Platform layer sits in the middle, and Cloud & Data Foundation sits below.

This role sits in the middle layer and builds the connective tissue that powers AI across Mitratech.

This role leads the combined AI Quality & Governance function, initially bringing together two closely related areas: Governance & Policy, and Evaluations & Observability. Over time these may grow into separate teams with separate leaders, but today they are tightly linked in both problem space and execution model.

You will own the platform that makes AI systems at Mitratech measurable, observable, governable, and production ready. The role combines platform engineering, applied AI quality, incident ownership, and practical governance implementation.

This is explicitly a hands-on leadership role. The team begins small — likely one to two direct reports — and you are expected to spend roughly half of your time writing and reviewing production code while the organization scales. Near-term success depends on a leader who wants to build as well as manage.

• Own the AI evaluations and observability platform — tracing, logs, dashboards, quality signals, and operational feedback loops for prompts, model calls, tool use, and user outcomes

• Design and operationalize automated and human-in-the-loop evaluation strategies, integrating regression checks for quality, safety, latency, and cost into engineering and release processes

• Establish the standards that define production-ready AI across the organization — evaluation criteria, release gates, incident playbooks, and long-term quality metrics

• Build and operate AI guardrails and policy enforcement capabilities: content controls, PII detection and redaction, audit logging, and request- or workflow-level policy checks

• Translate emerging governance and risk expectations into working engineering systems and platform controls rather than static documentation

• Own platform-level SLOs and tier-two incident support for AI behavior issues, partnering with product teams who remain first-line owners for features they ship

• Act as an internal authority on AI quality and governance and participate in customer-facing conversations where product quality, safety, observability, or governance posture must be explained credibly

• Hire, mentor, and grow the team over time — the combined function may later evolve into separate Quality/Observability and Governance/Policy teams

You have 8+ years of software engineering experience including meaningful experience leading engineers as a manager or technical lead. You have shipped production AI systems and have hands-on experience with the operational complexity they introduce.

• Strong experience designing and operating production backend systems and APIs

• Demonstrated hands-on experience building, shipping, or operating production AI systems — ideally including LLM-powered or agentic workflows

• Experience with AI observability, evaluation, or debugging systems — whether through platforms such as LangSmith or LangFuse, or through internally built equivalents

• Practical experience designing or operating AI guardrails: content filtering, redaction, access controls, or other controls around model or agent behavior

• Familiarity with AI governance and risk frameworks such as NIST AI RMF or ISO/IEC 42001, and the ability to engage thoughtfully with legal, compliance, and security stakeholders

• A strong bias toward hands-on execution, platform thinking, and creating paved roads for other teams

• Experience in legal technology, regulated SaaS, or other environments where auditability and defensibility matter

• Experience with privacy-sensitive systems and PII handling

• Experience participating in AI incident reviews, red-team exercises, or internal review boards for production AI systems

• Engineering environment primarily uses Python and TypeScript

• Observability tooling is being established — LangFuse experience relevant but not required

This is a high-impact role at the center of Mitratech's AI engineering organization. You will define what production-ready AI means across the platform, build the systems that enforce it, and serve as the senior authority on AI quality, safety, and observability. You will work closely with product and platform teams, set standards that apply org-wide, and help Mitratech ship AI that customers can trust.

If building that kind of foundational capability appeals to you, this role is worth a serious look.

We will disclose intended pay ranges in our job ads for US-based opportunities – This role can be performed 100% remote anywhere in the US. Anticipated Pay Range: $210K – $230K Annually USD