AI evangelist

you ExperienceFallon, MO

About The Position

We are seeking an experienced AI Evangelist with a deep understanding of the full Product Development Lifecycle (PDLC) to drive the adoption and integration of AI across our engineering and product teams. This role requires a strategic thinker and strong communicator who can coach teams, define standards, and demonstrate the tangible benefits of AI in real-world scenarios. You will be instrumental in transforming workflows, integrating AI solutions, and ensuring responsible AI practices are embedded throughout our delivery processes.

Requirements

  • Deep understanding of the full PDLC, from ideation and requirements through design, development, testing, security, deployment, and operations, including where AI can meaningfully augment each stage.
  • 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.
  • 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.

Nice To Haves

  • 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.
  • History of building repeatable assets such as playbooks, toolkits, templates, or reference models that scale beyond individual teams and reduce dependency on ongoing staff augmentation.
  • Tangible examples of AI-driven improvements you personally helped teams achieve, such as reduced cycle time, improved product quality, increased test coverage, or reduced operational toil.
  • Clear evidence of measurable delivery impact from prior AI initiatives, such as reduced development cycle time, increased test automation and coverage, improved production stability, or reduced operational toil.
  • Proven ability to translate experimentation into sustainable capability by leaving behind reusable patterns, standards, and self-sustaining practices.
  • Track record of helping organizations adopt AI responsibly, balancing speed with risk mitigation and embedding controls rather than treating governance as a separate gate.
  • Proven ability to leave behind self-sustaining capabilities, not dependency, by turning experimentation into repeatable, well-documented patterns.

Responsibilities

  • Embed directly with teams to 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 effectively and lead change, influencing executives and earning credibility with engineering and product teams, addressing concerns and driving adoption through visible outcomes.
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