AI Solution Lead

loom ai; United States; Hybrid; USD 120,000 - 160,000; Full time

Job summary

Loom AI deploys continuously learning AI decision systems inside large enterprises in regulated industries. The role is the translator between client goals and what gets built, surfacing nuances, constraints, and trade-offs through deep discovery and questions.

You're equally fluent in the other direction: guiding the technical team toward a solution that delivers the intended outcomes, and explaining reality to non-technical clients.

Qualifications

• 4–7 years in solution design, business analysis, or technical delivery in a consulting or enterprise context.
• Proven ability to translate between business goals and technical solutions — in both directions.
• Experience helping clients articulate and refine what they're trying to achieve and what success looks like.
• Hands-on experience with AI or ML systems — deployments, not just strategy decks.
• Comfortable presenting technical trade-offs and constraints to non-technical executives.
• Actively using AI tools in your own work — not just aware of them.

Responsibilities

• Go deep on what clients are trying to achieve — surface the nuance, constraints, and trade-offs that good discovery reveals
• Help clients articulate what success looks like in measurable terms — and track whether the solution is delivering it
• Guide clients toward realistic timelines and practical deployment approaches — explain why in terms that land
• Be the person the team goes to when they want to know why something is being built
• Catch early when a technical approach won't deliver the intended outcome — and bring a path forward
• Understand AI system design well enough to guide the technical team toward the right solution

Skills

Solution design

Business analysis

Technical delivery

AI/ML systems

Stakeholder communication

Regulated environment awareness

Job description

Contract-to-Hire 4–7 Years Remote · US Competitive Rate Equity on Conversion

loom ai deploys continuously learning AI decision systems inside large enterprises in regulated industries. The work lives at the intersection of complex business goals and sophisticated AI technology. We need someone who understands both sides deeply enough to be the person everyone on the project goes to when they want to know why something is being built — and whether it will actually solve the problem.

The Role

You are the translator — between what the client wants to achieve and what gets built.

In practice, this means you go deep enough on what a client is trying to achieve that you can surface things that may not have been fully articulated yet. Not because clients don't know what they need — but because good discovery reveals nuance, constraints, and trade-offs that only become visible when someone asks the right questions and listens carefully. That's you.

You're equally fluent in the other direction. You understand how AI systems work — how they're built, where they break, what's hard and what's easy — well enough to guide the technical team toward a solution that genuinely delivers the intended outcome. And you can explain the technical reality to a non-technical client: why a particular approach makes sense, why some things take longer than expected, what a realistic deployment looks like and why.

You're the person who catches it early when a technical approach won't deliver what was promised — and who knows how to fix it without derailing the engagement. You also own whether the solution delivers measurable value: you define what success looks like upfront, and you track whether the design is actually getting there.

What You'll Do Day to Day

Lead from the outcome. Build toward the solution.

Business & Discovery

• Go deep on what clients are trying to achieve — surface the nuance, constraints, and trade-offs that good discovery reveals
• Help clients articulate what success looks like in measurable terms — and track whether the solution is delivering it
• Guide clients toward realistic timelines and practical deployment approaches — explain why in terms that land
• Be the person the team goes to when they want to know why something is being built
• Catch early when a technical approach won't deliver the intended outcome — and bring a path forward

• Understand AI system design well enough to guide the technical team toward the right solution
• Explain technical constraints, trade-offs, and timelines clearly to non-technical client stakeholders
• Ensure the solution accounts for regulated environment realities — auditability, explainability, human oversight
• Work alongside our AI/ML engineers — pressure-test the design, not manage the team
• Use AI tools actively in your own work — not as a novelty but as a daily practice

What We're Looking For

AI fluency. Business empathy. Solution ownership.

Must-Haves

• 4–7 years in solution design, business analysis, or technical delivery in a consulting or enterprise context
• Proven ability to translate between business goals and technical solutions — in both directions
• Experience helping clients articulate and refine what they're trying to achieve and what success looks like
• Hands-on experience with AI or ML systems — deployments, not just strategy decks
• Comfortable presenting technical trade-offs and constraints to non-technical executives
• Actively using AI tools in your own work — not just aware of them

• Financial services or insurance background
• Experience with continuously learning or production ML systems
• Consulting firm background (Big 4, boutique, or strategy firm)
• Experience with AI governance frameworks or responsible AI practices

What We Offer

Hard problems. Real AI. Real upside.

Access

Direct access to founders — real ownership from day one

Exposure

Enterprise AI deployments in complex, regulated environments

Path

Full-time conversion based on performance and growth, with equity opportunity

Candidates must be authorized to work in the United States without visa sponsorship.