Senior Engineering Manager, AI Quality & Governance

Mitratech

1d•$210,000 - $230,000•Remote

About The Position

Mitratech is seeking a Senior Engineering Manager to lead the combined AI Quality & Governance function. This role is central to the AI Platform Organization, which aims to create a unified, safe AI platform powering legal workflows and driving productivity gains. The position involves owning the platform for making AI systems measurable, observable, governable, and production-ready. It combines platform engineering, applied AI quality, incident ownership, and practical governance implementation. This is a hands-on leadership role, initially with one to two direct reports, where the manager is expected to spend approximately half their time writing and reviewing production code while the organization scales. The ideal candidate will be a builder as well as a manager, focused on creating foundational capabilities for AI across Mitratech.

Requirements

8+ years of software engineering experience.
Meaningful experience leading engineers as a manager or technical lead.
Shipped production AI systems.
Hands-on experience with the operational complexity of AI systems.
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 (e.g., LangSmith, LangFuse, or internally built equivalents).
Practical experience designing or operating AI guardrails (content filtering, redaction, access controls, etc.).
Familiarity with AI governance and risk frameworks (e.g., NIST AI RMF, ISO/IEC 42001).
Ability to engage thoughtfully with legal, compliance, and security stakeholders.
Strong bias toward hands-on execution, platform thinking, and creating paved roads for other teams.

Nice To Haves

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.

Responsibilities

Own the AI evaluations and observability platform, including 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 standards for production-ready AI, including evaluation criteria, release gates, incident playbooks, and long-term quality metrics.
Build and operate AI guardrails and policy enforcement capabilities, such as 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.
Own platform-level SLOs and tier-two incident support for AI behavior issues, collaborating with product teams.
Act as an internal authority on AI quality and governance, and participate in customer-facing conversations.
Hire, mentor, and grow the team over time.