AI SDLC Engineer

Description Remote

Our client is launching an initiative to establish a consistent, measurable, and governed approach to using AI across the software development lifecycle. As an AI SDLC Engineer, you will embed with a Performance Squad to assess current workflows, improve AI-assisted engineering practices across development, testing, pull requests, and delivery, and help establish standards, governance controls, KPIs, and reusable documentation that can scale beyond the pilot.

We can facilitate w2 and corp-to-corp consultants. For our w2 consultants, we offer a great benefits package that includes Medical, Dental, and Vision benefits, 401k with company matching, and life insurance. Rate: $110.00 to $120.00/hr. w2

JN -102026-108994

Responsibilities

• Assess current engineering workflows, development tools, and AI usage.
• Identify opportunities to reduce manual effort and improve engineering productivity through AI.
• Apply AI-assisted practices across requirements refinement, code generation, automated testing, code review, pull-request validation, and technical documentation.
• Work directly with engineers on active code, pull requests, testing, and delivery decisions.
• Integrate AI into existing SDLC, CI/CD, DevOps, and quality-engineering workflows.
• Coach developers through hands-on implementation and day-to-day collaboration.
• Establish practical standards and controls for responsible AI-assisted software development.
• Maintain appropriate human ownership, independent review, traceability, and auditability for AI-assisted changes.
• Define and track KPIs related to AI adoption, delivery velocity, utilization, quality, and production impact.
• Create technical standards, playbooks, implementation guidance, and operating procedures.
• Translate technical findings and outcomes into clear updates for engineering leadership.
• Help establish an operating model that can be expanded to additional engineering teams.

Experience Requirements

• Senior-level, hands-on software engineering experience supporting production applications.
• Demonstrated experience using generative AI or AI-assisted development tools within active software engineering environments.
• Experience applying AI across multiple stages of the SDLC.
• Strong understanding of source control, pull requests, automated testing, CI/CD, and DevOps.
• Experience working directly with Agile or Scrum engineering teams during active sprint delivery.
• Ability to collaborate on active code, technical decisions, testing, and delivery workflows.
• Experience assessing engineering processes and implementing practical improvements.
• Experience improving workflows, quality, productivity, or delivery speed through AI.
• Understanding of responsible AI principles including accountability, security, quality controls, independent review, traceability, and auditability.
• Experience developing or implementing engineering standards, AI usage guidelines, governance controls, playbooks, or operating procedures.
• Experience defining or measuring outcomes related to AI adoption, productivity, velocity, quality, utilization, or production impact.
• Strong coaching skills and ability to drive adoption through collaboration.
• Strong written and verbal communication skills for technical and leadership audiences.
• Based in and authorized to work in the United States.
• Ability to work remotely with flexible availability across Eastern and Pacific Time zones.

Education Requirements