Solutions Engineer, AI

Valence has built the only AI native coaching platform for enterprise, offering personalized, expert, and human-like guidance and support to any leader or employee. We’re not just talking about the future of work — we’re building it now, with the most innovative Fortune 500 companies across healthcare, financial services, manufacturing, and technology.

Our focus is on the problems that actually decide whether AI changes how organizations operate — the ones with no playbook, no obvious answers, and no guarantee of success. If you want to be part of the small group that defines how AI transforms the future at a global scale, this is your chance.

And this isn’t for everyone. We’re not looking for people who want predictability or incremental progress. We only want those who are restless at the edge of what’s possible, who get bored when things feel “done,” and who are driven to redefine what AI can mean for leaders, companies, and the world. Because at Valence, the work worth doing is the kind that redefines work itself.

This role will lead enterprise solutions for Nadia, our AI coach, by adapting and delivering tailored implementations for complex customer environments. You will design, implement, and evaluate high-impact workflows (prompts, memory and knowledge patterns, coaching flows), balance bespoke and reusable architectures, and build the tooling and evaluation discipline that let us scale enterprise AI deployments. This role sits at the heart of Valence.

You will collaborate closely with Product, AI Research/Applied AI, and Engineering to ensure our most advanced enterprise AI systems are safe, performant, and aligned with real user outcomes. This is a hybrid role that combines product sense, technical grounding, and strong delivery instinct. It is ideal for someone who loves to build, ship, and iterate.

We're the only company pioneering leadership coaching for large enterprises in an AI-first way. Our mission is to transform how the world's biggest companies approach learning and development, helping teams work better together through AI-powered personalization that adapts to individual goals and organizational culture using the latest advances in machine learning and natural language processing.

We've been featured in Harvard Business Review, TIME, World Economic Forum, Financial Times, Forbes and an Inc. 5000 fastest-growing private companies in America. Our clients represent the most diverse and sophisticated enterprise AI implementations globally, including Coca-Cola, Delta, Nestlé, General Mills, Service Now, Schneider Electric, Deutsche Telekom, AstraZeneca, Prudential, CVS and Bristol Myers Squibb.

Working at Valence means you'll work directly with Fortune 500 technology leaders, building expertise through the most complex enterprise deployments while gaining insight into diverse organizational approaches to AI transformation. These aren't just any enterprise clients - they're the companies defining what AI-first business transformation looks like across every major industry.

• Own end-to-end AI solutions: Lead the full lifecycle for enterprise-grade workflows, from discovery and design through implementation, evaluation, and iteration.
• Architect for reuse: Identify repeatable patterns, modularize components, and define when to productize; communicate tradeoffs across speed, quality, and maintainability.
• Drive quality and evaluation: Define prompting standards, guardrails, and success metrics (accuracy, tone, safety, outcome quality). Build lightweight evaluation frameworks that scale across clients.
• Make hard tradeoffs: Balance speed vs. scalability; protect the platform from over-engineering while ensuring customers see real value quickly.
• Collaborate deeply: Partner with Product, AI Engineering, and Coaching SMEs to deliver solutions with measurable impact.
• Mentor and level up others: Guide associates or EMs learning prompting and integration skills; contribute to playbooks, templates, and internal training.
• Measure outcomes: Track deployment speed, adoption, satisfaction, and quality; identify opportunities for reusability and efficiency gains.