Job Title: Principal AI Engineer
Location: NYC
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 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/Google Cloud Platform/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 and foster an inclusive environment with people at all levels of an organization
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