AI Innovation Adoption Lead

Pogue Construction

$90K — $130K *
Enterprise Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • Bachelor's degree in Technology, Construction Management, or a related field.
  • 3-6 years experience in AI, technology, data, analytics, and software.
  • Strong organizational and administrative skills.
  • Proven ability to rapidly prototype using modern AI tools and APIs.
  • Fluency in prompt engineering and model evaluation within AI ecosystems.

Responsibilities

  • Track and evaluate new AI capabilities against real-world problems at Pogue.
  • Build rapid proofs-of-concept to test innovation ideas.
  • Develop and pilot working solutions demonstrating measurable value.
  • Transform leadership’s vision into practical prototypes for evaluation.
  • Transition successful prototypes to delivery teams for further development.

Benefits

  • Mentorship opportunities to influence and guide AI champions and users across the organization.
  • Exposure to cutting-edge AI technologies and innovation initiatives.
  • Collaboration with cross-functional teams to enhance project outcomes.
  • Flexibility to work in a fast-paced, dynamic environment.
Full Job Description
JOB DESCRIPTION:

Education & Experience:
  • A bachelor's degree in Technology, Construction Management, or a related field.
  • 3-6 years experience with AI, technology, data, analytics, and various software.

Summary of Position:

The AI Innovation & Adoption Lead will lead Pogue's emerging AI and edge innovation for the enterprise AI initiative. The AI Lead will take leadership's vision and push the envelope; scouting new AI capabilities, proving them through rapid prototypes and pilots, then handing proven concepts to the delivery teams to build and scale.

Primary Responsibilities:

Emerging AI Scouting:
  • Track, evaluate, and pressure-test new AI capabilities (models, agents, tooling) against real Pogue problems.
  • Maintain a living view of the AI landscape and surface what's worth pursuing before the market catches up

Rapid Prototyping & R&D:
  • Build proofs-of-concept fast
  • Push the envelope on what's possible
  • De-risk frontier capabilities before enterprise investment.
  • Document lessons learned

Edge Innovation & Piloting:
  • Turn promising ideas into working pilots that demonstrate clear and measurable value
  • Design pilots to fail fast and cheap where they don't hold up, and amplify those that do.

Vision Into Proof:
  • Turn leadership's vision into working prototypes that prove real value
  • Translate ambiguous vision into something to put in front of an executive.

Hand off & partner:
  • Transition proven concepts to the Solutions Architect and delivery teams to build, harden, and scale without losing the intent of the original solution.

Technical guidance:
  • Mentor AI champions, power users, and analysts through expertise and influence.

Required Skills & Expectations:
  • Strong organizational and administrative skills.
  • Effective verbal and written communication skills.
  • Ability to work with cross-functional teams and liaise between departments.
  • Attention to detail and strong problem-solving skills.
  • Ability to maintain confidentiality and professionalism.
  • Flexibility and adaptability in a fast-paced environment.
  • Strong time management and organizational skills.
  • Demonstrated ability to build working prototypes using modern AI tools and APIs (LLMs, agents, automation platforms)
  • Fluency with prompt engineering, model evaluation, and AI tooling ecosystems (e.g., OpenAI, Anthropic, LangChain, vector databases, or equivalents)
  • Experience running structured pilots or proofs-of-concept with clear success criteria
  • Strong written and verbal communication - able to translate technical findings for non-technical stakeholders at the ELT level
  • Comfort working in ambiguity with limited oversight
  • Preferred: Experience working within or alongside enterprise IT or software delivery teams
  • Preferred: Familiarity with change management or technology adoption frameworks
  • Preferred: Experience with low-code/no-code platforms in addition to traditional development environments

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