Principal AI Engineer

Mitratech

22h•$200,000 - $220,000•Remote

About The Position

At Mitratech, we are a team of innovators focused on building world-class products that simplify operations in the Legal, Risk, Compliance, and HR functions. We are a close-knit, globally dispersed team that thrives in an ecosystem that supports individual excellence and takes pride in its diverse and inclusive work culture centered around great people practices, learning opportunities, and having fun! Our culture is the ideal blend of entrepreneurial spirit and enterprise investment, enabling the chance to move at a rapid pace with some of the most complex, leading-edge technologies available. For over 35 years, the experts at Mitratech have been focused on solving the complex needs. Today, we serve 20,000 client companies of all sizes globally, representing 30% of the Fortune 500 and over 500,000 users in over 160 countries. As we continue to grow, we’re always looking for resourceful, enthusiastic, and fresh perspectives. Join our global team and see what makes Mitratech a truly exceptional place to work! Job Overview The Principal AI Engineer is a senior individual-contributor and technical-leadership role on the AI and Platform team within Mitratech’s Legal Solutions division, reporting to the Senior Director, AI. The role is aligned to the organization rather than to a single team: you set technical direction across multiple services and teams, define the AI platform patterns the engineering organization builds on — agent orchestration, tooling, governance hooks, and evaluation surfaces — and stay deeply hands-on, writing production code every day. You will operate in two primary modes: as a technical advisor and expert who helps teams solve problems and set architecture and solutions for specific initiatives, and as an embedded resource who aligns with a particular engineering team for an extended period to implement and deliver key functionality or solve highly complex technical problems before moving on to the next problem or team. In practice, your day to day will likely be a combination of both.

Requirements

Principal-level, hands-on experience as a technical leader who sets direction across teams while still writing production code, with deep expertise across the modern Python AI stack.
Deep expertise in Python and backend service development — building and operating production APIs and services.
Cloud platform engineering — designing and running cloud-native, event-driven systems (AWS preferred).
GenAI / LLM application engineering — RAG, embeddings, prompting, and guardrails on managed model platforms.
Agent tooling and integration protocols — agent orchestration frameworks and tool/context protocols such as MCP, including the design of agent coordination patterns.
Data persistence — across relational, key-value, document, and warehouse stores, with async data access and schema migration.
Application security and identity — authentication, authorization, secrets management, and policy enforcement, ideally in a multi-tenant context.
Automated testing and quality engineering — across unit, integration, and end-to-end layers.
Modern developer-tooling and code-quality practices — linting, typing, formatting, and reproducible builds.
Comfortably work with Infrastructure as Code, containerization and orchestration, CI/CD and release automation, and observability and evaluation for LLM and backend systems.

Nice To Haves

frontend / web UI development
data warehouse engineering
NoSQL / document databases

Responsibilities

Set technical direction across multiple services and teams, operating with broad autonomy
Define the AI platform patterns other teams build on — agent orchestration, tooling, governance hooks, and evaluation surfaces
Own reliability, testing, CI/CD, and operational standards across multiple teams
Provide technical leadership across teams, and influence staffing and roadmap priorities
Serve as a technical advisor and expert to teams, and embed within teams to deliver complex, high-value functionality
Stay hands-on — design and build production systems in Python across the AI stack
Define patterns and mentor engineers across teams, raising the technical bar