Principal AI Engineer

**Job description**

At <our consulting company>, 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.

<Our consulting company> 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 <our consulting company> 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 methodologies and cross-functional product team collaboration.

**Preferred / Additional Qualifications**

• Experience applying AI/ML in business consulting, advisory, or professional services contexts.
• Familiarity with AI service interface and gateway design patterns, including emerging AI integration protocols.
• Contributions to open-source AI/ML projects, publications, or active involvement in technical communities.
• Advanced certifications in AI, deep learning, cloud architecture, or security (e.g., AWS/GCP/Azure ML, CISSP).
• Experience defining AI compliance controls for SOC2, ISO 27001, or TISAX frameworks.
• Demonstrated enthusiasm for developer education — writing internal guides, running workshops, or building internal tooling communities.
• Proficiency in additional languages is a plus (Go, Typescript)
• Demonstrated ability and enthusiasm to mentor and uplift junior team members or peers
• Willingness to work outside of normal business hours, and in particular as unique projects/needs arise.
• Ability to work full time in an office and remote environment; physically able to sit/stand at a computer and work in front of a computer screen for significant portions of the workday
• Must become familiar with, and promote and abide by, our Core Values as defined by the <our consulting company> and foster an inclusive environment with people at all levels of an organization