AI Value Engineer - Public Trust

AI Value Engineer
Position Overview

PhoenixTeam is a remote-first organization seeking a versatile, high-impact AI Value Engineer to join our AI services team. This is not a narrow role — it's designed for someone who thrives in ambiguity and can move seamlessly between client delivery, rapid experimentation, hands-on education, and internal capability building.

The AI Value Engineer will lead the application of generative AI to real-world challenges — and quantify the business value it delivers — particularly in complex, regulated environments, working closely with mortgage industry clients. This role calls for a proactive self-starter who can turn insight into action, operate independently, and lead engagements, experiments, and learning efforts with minimal oversight. Mortgage industry experience is preferred; candidates without it should be prepared to ramp up on the domain quickly.
Key Functions

- Lead client engagements to scope, prototype, and deliver GenAI-powered workflows.

- Translate business and operational pain points into LLM-based solutions.

- Run discovery sessions, use case sprints, and prompt engineering labs with stakeholders.

- Establish current-state baselines — cycle time, cost per transaction, error and rework rates — before solutions are built.

- Build and defend business cases that size expected impact and the assumptions behind it.

- Measure realized value post-deployment and report outcomes to client executives.

- Stand up fast-cycle experiments and proofs of concept using tools such as ChatGPT, Claude, Gemini, or open-source models.

- Package successful experiments into reusable artifacts, including prompt libraries, workflows, and solution playbooks.

- Collaborate with subject matter experts, compliance, and technical partners to validate and refine concepts.

- Facilitate live GenAI learning experiences, including intro sessions, role-based labs, and problem-solving workshops.

- Build and deliver enablement materials such as guides, templates, videos, job aids, and micro-learning tools.

- Act as a trusted advisor to teams navigating AI adoption, capability gaps, and workflow redesign.

- Launch and operate internal or client-specific “GenAI Labs” to drive adoption and learning-by-doing.

- Capture real-world insights to inform product, content, and go-to-market strategies.

Minimum Qualifications

- 3–5 years of experience in consulting, product enablement, innovation, or applied business strategy.

- Demonstrated ability to work independently, make decisions, and lead client work without constant oversight.

- Hands-on experience using generative AI for real work, including building prompts, workflows, and proofs of concept.

- Experience building business cases — establishing baselines, sizing impact, and presenting ROI to executive stakeholders.

- Excellent facilitation and storytelling skills, with the ability to bridge business, compliance, and technical stakeholders.

- Ability to think and act quickly in fluid environments, with strong executional follow-through.

- Self-directed learner with high curiosity and a bias toward action.

Preferred Qualifications

- Mortgage, fintech, or other regulated industry experience (preferred, not required — willingness to learn quickly is essential).

- Familiarity with AI safety, governance, and compliance.

- Comfort working with model APIs, retrieval patterns, and evaluation methods for testing output quality at scale.

- Ability to use or teach tools such as ChatGPT, Claude, Gemini, Notion, Airtable, Zapier, LangChain, or similar.

- Experience in startups, consulting, internal strategy, learning & development (L&D), or innovation teams.

What Success Looks Like

- Clients move from “what is this?” to “we're using this” — with your guidance.

- Experiments are executed, refined, and scaled into reusable solutions.

- GenAI learning labs unlock energy, capability, and adoption across the enterprise.

- Every engagement carries a d