Principal AI Engineer

Role Description

As a Principal AI Engineer, you will:

• Set the AI Technical Direction: Own the architecture for AI capabilities across HotDocs - model management, LLM and agent orchestration, retrieval strategy, evaluation, cost and latency management - and translate it into a pragmatic delivery roadmap.
• Deliver Enterprise AI Features: Take new AI-powered features from prototype to production at enterprise scale, writing clean, maintainable code in .NET Core and React and holding the bar for performance, security, and readability.
• Drive AI Adoption in the SDLC: Lead how we use AI across engineering - coding assistants, agentic workflows, test generation, code review, and documentation - selecting tooling, defining safe and effective usage patterns, and measuring the impact on delivery.
• Build Trustworthy AI: Establish evaluation harnesses, guardrails, observability, and AI governance practices so that AI features are accurate, explainable, and safe for use in regulated, compliance-heavy environments.
• Bring Deep Technical Expertise: Apply strong .NET and React ecosystem knowledge to complex problems, modernize and refactor legacy code where it blocks AI integration, and improve system scalability and reliability.
• Lead and Mentor: Raise the AI capability of the wider engineering group through code reviews, design reviews, pairing, brown-bag sessions, and clear written guidance.
• Influence Across the Business: Partner with product management, architecture, security, and customer-facing teams to shape the AI roadmap, evaluate build-versus-buy decisions, and set realistic expectations for what AI can deliver.
• Enhance DevOps and AI Ops: Extend CI/CD pipelines to cover AI workloads - prompt and model versioning, automated evaluation gates, monitoring, and cost tracking - working closely with DevOps engineers.
• Focus on the User: Ensure AI features solve real customer problems and deliver a great experience through attention to detail, responsiveness, transparency, and accessibility.

Qualifications

• A Technical Leader: You set direction without needing authority, build consensus across teams, and communicate clearly with technical and non-technical peers.
• An AI Practitioner, not a Spectator: You have shipped AI features to real users, keep pace with a fast-moving field, and can tell genuine capability from hype.
• Evidence-Led: You care about maintainable code, testing, and measurable outcomes - you evaluate AI systems with data rather than intuition.
• Adaptable and Pragmatic: You balance long-term architectural goals with the practical needs of a sprint-driven environment, and you know when a simple solution beats a model.
• Security-, Privacy- and Performance-Minded: You build with scalability and resilience in mind, using secure-by-design principles, and you treat data privacy and responsible AI as first-order concerns.

Requirements

• 12 or more years of professional software development experience, including time in a principal, lead, or staff-level technical role.
• Strong skills in .NET Core (C#) and React (TypeScript) or similar SPA frameworks - this remains a hands-on engineering role.
• Demonstrable experience designing and shipping production AI solutions - LLM integration, prompt engineering, RAG, MCP, and agentic or tool-calling systems.
• Hands-on experience with cloud AI platforms and services (e.g. Azure OpenAI / AI Foundry, or equivalent) and with orchestration frameworks such as Semantic Kernel.
• Experience building and maintaining REST APIs.
• Proficiency with Entity Framework and Azure SQL (or SQL Server).
• Experience evaluating and improving AI system quality - test sets, benchmarking, human review loops, and handling non-deterministic behavior.
• Understanding of web applications and AI-specific security, including secure coding, prompt injection, and safe handling of sensitive customer data.
• Experience using Git and collaborating through modern workflows (e.g., pull requests, branching strategies).
• Experience with CI/CD pipelines (Azure DevOps or similar).
• Comfortable working in agile teams using tools such as Jira and Confluence.
• Practical experience using AI tooling within the SDLC (e.g. coding assistants, agentic developer tools) and a view on how to adopt it well across a team.
• A track record of technical leadership - mentoring senior engineers, leading design reviews, and influencing roadmap and architecture decisions.

Benefits

• A collaborative, supportive, and learning-focused work culture.
• The chance to shape an AI strategy end to end, from architecture through to production, at enterprise scale.
• Opportunities to grow your technical skills and career path.
• Remote-first flexibility with optional in-person collaboration sessions.
• Competitive benefits and a chance to impact how global organizations automate critical legal and compliance workflows.

Company Description

At Mitratech, we’re a team of engineers passionate about building world-class products that empower Legal, Risk, Compliance, and HR professionals at Fortune 100 companies. We thrive in a global, inclusive culture that values innovation, collaboration, and technical excellence.