# Principal AI Engineer at Phizenix > United States · Principal · ML / AI · open. Source: https://alderhq.app/jobs/greenhouse%3Aphizenix%3A5422041008 (read 2026-11-11). ## Facts (observed) - Company: [Phizenix](https://alderhq.app/companies/phizenix) - Location text: Midtown Manhattan, New York City; Phizenix - Where it can be done from (inferred): United States (evidence: "Location: Midtown Manhattan, New York City; Phizenix") - Posted: 2026-09-11 (60 days ago) - First seen by alder: 2026-11-07 · last verified: 2026-11-08 - Reposted: 0 times · edited: 0 times - Apply on the employer's site: https://job-boards.greenhouse.io/phizenix/jobs/5422041008 - Skills listed (inferred): Python, Docker, Terraform, LLMs, Distributed systems ## Pay and sponsorship - Posted pay: not posted - Market band for similar posted roles (New York, n 231): p25 $185k, median $230k, p75 $275k ## Description (the employer's text) ### Job description 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. --- Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/greenhouse%3Aphizenix%3A5422041008 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.