At AlixPartners, 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. AlixPartners 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 AlixPartners’ 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.

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.