Principal AI Engineer

At , we solve the most complex and critical challenges by moving quickly from analysis to action when it really matters; creating value that has a lasting impact on companies, their people, and the communities they serve. We hold ourselves accountable by providing space for authenticity, growth, and equity for everyone.

has embraced a hybrid work model to provide flexibility and support work-life integration. Travel is part of this position, but frequency may vary based on client, team, and individual circumstances. Relocation assistance is not available for this position. **About the Role** The Principal AI Engineer sits at the intersection of software engineering, data science, platform architecture, and AI governance. You will be the technical owner of how AI/ML engineering is designed, built, governed, and shipped across a portfolio of products serving all of domains. This is a hands-on engineering and technical leadership position. You will move fluidly between writing production code, architecting multi-tenant AI services, building internal developer tooling, leading security and governance design, and mentoring engineering teams. Your success is measured by team-level outcomes — scalable patterns that outlast your direct involvement. **What You'll Do** **AI Productization & Platform Engineering** - **Design and own the firm's AI productization & governance playbook,** covering service patterns, security/compliance standards, model evaluation rubrics, and production-readiness criteria. - **Build and maintain reusable internal tooling,** including AI service scaffolding, evaluation and monitoring tooling, and data infrastructure — designed for team adoption without ongoing hand-holding. - **Establish AI agent governance policies** covering agent permissions, code execution controls, access to internal systems, and human-in-the-loop enforcement. - **Partner with Security, Legal, and Compliance** to define SOC2/ISO-aligned AI controls, vendor DPA requirements, and prompt data classification policies. - **Establish standardized deployment patterns** using containerization, infrastructure-as-code, and CI/CD pipeline templates reusable across teams. **Developer Experience & Engineering Excellence** - **Champion AI-assisted development practices across the engineering org,** including LLM-integrated development workflows, test-driven development patterns, and reusable tooling standards that scale across teams. - **Codify modern software development standards** (CI/CD, DevOps, testing, delivery quality) referenced by multiple teams as a baseline for new or re-platformed products. - **Mentor engineers and tech leads** with observable improvement in delivery consistency, design quality, and production readiness rigor. **Cross-Functional Leadership & Stakeholder Influence** - **Serve as the go-to technical authority** on AI/ML, platform architecture, and engineering practices — regularly consulted by senior stakeholders at the design and strategy stages. - **Bridge technical and non-technical stakeholders,** translating complex architectural decisions, AI risk topics, and platform tradeoffs into clear, actionable guidance. **What You'll Need** **Required** - 15+ years in software engineering, data science, or a closely related technical field. - Bachelor's degree or higher in Computer Science, Engineering, or a related field. - Deep expertise in AI/ML frameworks and the Python ecosystem, with hands-on experience deploying models to public cloud infrastructure. - Demonstrated experience designing and operating multi-tenant AI services and LLM integrations in production. - Proven track record leading microservices architecture — decomposing monoliths, defining service contracts, and operationalizing CI/CD for distributed systems. - Strong hands-on command of containerization (Docker), infrastructure-as-code (Terraform), and modern DevOps practices. - Substantive experience with AI/LLM security — including prompt injection, data boundary enforcement, model supply chain risk, and AI-specific threat modeling. - Strong problem-solving skills, especially in building governance frameworks, evaluation rubrics, and reusable platform patterns at scale. - Excellent written and verbal communication skills in English; ability to translate complex technical topics to diverse audiences, including executive stakeholders. - Experience with Agile meth...