Principal AI Engineer

About The Role As a Principal AI Engineer, you will sit at the intersection of software engineering, data science, platform architecture, and AI governance. You will serve as the technical owner for how AI/ML engineering is designed, built, governed, and shipped across our client’s entire product portfolio. This is a hands-on leadership position where you will fluidly transition between writing production code, architecting multi-tenant AI services, building developer tooling, and leading security design. Your success is measured by creating scalable patterns that outlast your direct involvement.

What You’ll Do

• AI Productization & Platform Engineering: Design and own our AI productization and governance playbook, covering service patterns, compliance standards, and production-readiness criteria. You will build reusable internal tooling, such as AI service scaffolding and monitoring tools, to enable team adoption without ongoing hand-holding.
• Governance & Security: Establish AI agent governance policies, including permissions and human-in-the-loop enforcement. You will partner with Security, Legal, and Compliance to define SOC2/ISO-aligned AI controls and prompt data classification policies.
• Engineering Excellence: Champion AI-assisted development practices and codify modern software standards (CI/CD, DevOps, testing) that serve as a baseline for all products.
• Leadership & Mentorship: Serve as the go-to technical authority on AI/ML and platform architecture for senior stakeholders. You will mentor engineers and tech leads to improve delivery consistency and design quality.

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)