Compensation
$141,600-$177,000/yrDescription
Scale AI's Advisory practice is the most forward-leaning bet in our go-to-market motion. We're not waiting for clients to hand us a scope — we get in front of the decision, shape the right AI problems before a build begins, and make Scale the obvious partner for what comes next.
Advisory is the structured answer to the question enterprises are already asking us: "What should we build, and where do we start?" It's a discovery and scoping phase that runs before delivery — designed to land bigger contracts, drive more predictable execution, and accelerate expansion. By 2027, it will be Scale's default first engagement with new enterprise clients.
As an AI Advisory Consultant, you sit at the center of every engagement — paired with a Principal, producing the research, synthesis, impact sizing, and workshop materials that shape the work, and pressure-testing the team's assumptions. You also run the engagement day-to-day — owning the timelines, trackers, and coordination across Solutions Engineering and Design, and acting as the single source of truth that keeps everything on track from kickoff to final readout. This is a delivery role; you own real parts of the advisory work and partner closely with the Principal to deliver the engagement. It's a direct path into the AI Advisory Principal track.
What You'll Own
You're at the center of every engagement — doing the work and keeping it on track.
- Deliver the core advisory work. You produce the output the engagement runs on — market research, impact sizing, synthesis, and workshop materials — working alongside the Principal.
- Run the engagement day-to-day. You own the timelines, trackers, and single source of truth — monitoring open items and follow-ups across Solutions Engineering and Design, and keeping the engagement on track from kickoff to final readout. Working closely with the Solutions Engineering workstream, you weave their technical and feasibility findings into the readouts so the engagement tells one coherent story.
- Build the case ahead of client conversations. You develop the research and supporting materials that set up pre-sales conversations to land, and support the Principal in building out vertical thought leadership.
- Turn each engagement into reusable knowledge. You own the debrief notes, findings write-ups, and structured hand-offs after each engagement, and you contribute the patterns and materials that improve the motion and playbook.
- Build the AI workflows that make us faster. You spot where the team's work can be automated or templatized — recaps, status tracking, synthesized readouts, reusable materials — and you build those AI-powered solutions, not just flag them. You also set up baseline measurement and tracking.
Qualifications
Ideally, you’d have
- Consultant equivalent experience at a Tier 1 firm (McKinsey, Bain, BCG ideally); 3+ years of work experience. Experience on AI strategy or transformation projects strongly preferred.
- A track record of structured, analytics-driven problem solving — turning messy, ambiguous inputs into a clear, defensible point of view.
- Excellent communication — produces clean, exec-ready first drafts of findings and materials that need little editing.
- A history of diligence and organization across multiple workstreams — owns the trackers and details so nothing slips, even under time pressure.
- Technical credibility. No engineering degree required. You are curious enough to push back on engineering leads when the architecture or the accuracy story doesn't hold up.
- Hands-on with GenAI in daily work — can point to concrete examples of using AI tools to work faster.
- Commercial instinct. You think in business levers. You articulate ROI without prompting and spot upsell logic the Account Executives missed.
- Willingness to travel 30-60 percent, which can include international trips depending on the account.
Nice to Have
- 0-to1 experience developing or deploying GenAI applications in an enterprise setting.
- Exposure to enterprise AI or one of Scale's target verticals (Consumer, Financial & Professional Services, Healthcare & Life Sciences).
- Experience designing and synthesizing design-thinking workshops.
Stack
- Posted
- Jul 16, 2026
- Last seen
- Jul 16, 2026
- First seen
- Jul 16, 2026
