AI/ML Lead Engineer - W2 Position

AI / ML Lead Engineer Hybrid 4 days/week Minneapolis, MN 12mo Contract W2 Position Role Summary This role leads the technical execution of AI delivery while remaining deeply handson. The lead ensures the team builds solutions that are scalable, secure, and productionready. Business Challenge This Role Solves Accelerates delivery on a greenfield AI program Reduces technical risk and rework Aligns business needs with technical execution Core Responsibilities Design endtoend AI solutions from requirements to production Mentor and guide AI/ML engineers on best practices Break business problems into executable technical work Review architecture, code, and deployment approaches Partner closely with business stakeholders and program leadership Ensure AI solutions meet security, compliance, and reliability standards Required Technical Experience 7 to 10 years of software engineering experience Proven delivery of AI solutions into production environments Experience leading or mentoring engineers Strong background in cloud, APIs, and enterprise systems Comfortable working directly with business partners Top Skills Endtoend AI solution architecture Technical leadership and mentorship Production deployment Communication and collaboration Additional Technical Skills Sprint planning and estimation Risk assessment and mitigation Documentation and standards definition Stakeholder management Top Skills Details

• EndtoEnd AI Solution Design:

  Designing AI solutions from business requirements, Defining architecture, patterns, and standards, Evaluating tradeoffs between speed, risk, and scale

• Deep Production Experience:

  Proven experience deploying AI into enterprise environments, Understanding operational risks and mitigations, Knowing what breaks in production and why

• Technical Leadership and Mentorship:

  Guiding engineers on architecture and implementation, Reviewing designs and code, Helping engineers ramp up on deployment practices

• Business Communication:

  Translating business problems into technical plans, Explaining AI behavior to nontechnical stakeholders, Aligning delivery with business priorities
• Experience deploying production ready solutions in financial services or similar highly regulated industry Interview Information 1: Hiring manager screen 2: Technical interview (handson or scenariobased), Deep technical panel with engineers, 3.

Optional coding round if needed Focus is on: Realworld problem solving Production experience Ability to explain AI decisions clearly Business Challenge Ensures AI solutions are scalable, reliable, and aligned to business priorities. Accelerates adoption while reducing risk and rework.