AI Adoption Coach – Product Development Lifecycle (PDLC) with Security Clearance

About the role

This role is a hands-on, embedded individual contributor that acts as a guide and coach to product and engineering teams as they adopt AI across the Product Development Lifecycle (PDLC).

Responsibilities

• Embed directly with teams and coach through hands-on application, working shoulder-to-shoulder with engineers, product managers, and QA to apply AI in real scenarios.
• Define and operationalize AI standards, patterns, and best practices, including usage guidelines, prompt conventions, reference architectures, and reusable templates.
• Design and deliver enablement programs, including playbooks, training materials, workshops, and hands-on coaching that translate AI concepts into practical day-to-day application.
• Integrate AI solutions into existing toolchains, such as IDEs, CI/CD pipelines, testing frameworks, and monitoring platforms, including rapid prototyping to demonstrate value.
• Communicate and influence executives and engineering/product teams, addressing concerns and driving adoption through visible outcomes.
• Define a phased roadmap for AI adoption across the PDLC that aligns with business objectives and ties each initiative to clear value.
• Bridge product, engineering, devops, security, and compliance, ensuring AI improvements are coordinated rather than siloed.
• Redesign workflows to fully leverage AI capabilities, not simply automate existing steps.
• Drive toward measurable results while maintaining quality, safety, and compliance, and continuously refine approaches based on feedback and data.

Requirements

Ten or more years of experience in software development, platform engineering, or technology consulting, with significant exposure to AI-enabled or DevOps-driven transformation initiatives.

Demonstrated success working in large, complex, and regulated enterprise environments, with hands-on experience navigating governance, security, and compliance constraints.

Prior experience acting as a change agent, program lead, consultant, or internal champion, influencing teams without formal authority and engaging both senior leaders and delivery teams.

Qualifications

Strong working knowledge of modern AI tooling, particularly generative AI assistants, automation frameworks, developer assistances (e.g. GHCP, Claude Code), and current / emerging best practices, with the ability to evaluate and adopt tools pragmatically rather than by vendor alignment.

Solid grounding in responsible AI, including data privacy, security, model risk management, and ethical principles, with experience embedding governance and compliance controls directly into delivery workflows.

Familiarity with defining and tracking metrics to measure AI impact on engineering and product outcomes, such as cycle time, defect rates, test coverage, and operational stability.

Skills

• Ability to embed directly with teams and coach through hands-on application, working shoulder-to-shoulder with engineers, product managers, and QA to apply AI in real scenarios.
• Ability to define and operationalize AI standards, patterns, and best practices, including usage guidelines, prompt conventions, reference architectures, and reusable templates.
• Proven capability to design and deliver enablement programs, including playbooks, training materials, workshops, and hands-on coaching that translate AI concepts into practical day-to-day application.
• Technical proficiency in integrating AI solutions into existing toolchains, such as IDEs, CI/CD pipelines, testing frameworks, and monitoring platforms, including rapid prototyping to demonstrate value.
• Strong communication and change leadership skills, with the ability to influence executives and earn credibility with engineering and product teams, addressing concerns and driving adoption through visible outcomes.
• Strategic thinker who can define a phased roadmap for AI adoption across the PDLC that aligns with business objectives and ties each initiative to clear value.
• Strong cross-functional influencer capable of bridging product, engineering, devops, security, and compliance, ensuring AI improvements are coordinated rather than siloed.
• Systems-oriented problem solver who can redesign workflows to fully leverage AI capabilities, not simply automate existing steps.
• Outcome-focused and adaptable leader who drives toward measurable results while maintaining quality, safety, and compliance, and continuously refines approaches based on feedback and data.

Benefits

Full Benefits Package
10 Days PTO
6 Sick leaves
10 Paid Holidays
401K