About the role

What will you do at Midwestern?

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.

Location: New York (Hybrid - Midtown)

Work Arrangements: Open to 1099, C2C or W2

Duration: 12 month contract - high likelihood of extension based on performance

Travel: None

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
• 12+ 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 preferred.
• 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.

Which skills does this role require?

LLM IntegrationAI GovernanceSecurity ComplianceData InfrastructureTechnical LeadershipPrompt EngineeringAI EngineeringMachine LearningSOC2ISO 27001Data ClassificationPlatform ArchitectureSoftware EngineeringData ScienceModel EvaluationTypeScriptAWSGCPAzureLLMs

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