Valence

Valence

Solutions Engineer, AI

New York, New York

Sponsorship not specifiedDetected 6 days ago
Machine LearningNLPLLMsStakeholder ManagementResearchLeadershipMentoring

About the role

  • This is a hybrid role that combines product sense, technical grounding, and strong delivery instinct.
  • We're the only company pioneering leadership coaching for large enterprises in an AI-first way.
  • We've been featured in Harvard Business Review, TIME, World Economic Forum, Financial Times, Forbes and an Inc.

Responsibilities

  • Own end-to-end AI solutions: Lead the full lifecycle for enterprise-grade workflows, from discovery and design through implementation, evaluation, and iteration.
  • Drive quality and evaluation: Define prompting standards, guardrails, and success metrics (accuracy, tone, safety, outcome quality). Build lightweight evaluation frameworks that scale across clients.
  • Collaborate deeply: Partner with Product, AI Engineering, and Coaching SMEs to deliver solutions with measurable impact.
  • LLM/AI experience: prompt design, evaluation, and deployment of LLM-powered systems. Understanding of memory/knowledge retrieval and safety/guardrails.
  • Build expertise in enterprise AI implementation across Fortune 500 companies and multiple industries
  • Top-up grants as we scale and you deliver exceptional performance - your compensation grows alongside your impact

Requirements

  • 3+ years in solutions engineering, forward-deployed engineering, or consulting engineering, ideally with enterprise-facing experience.
  • Systems & judgment: track record of deciding what should be bespoke vs. reusable, designing for modularity without over-engineering.
  • You know when to push back and when to ship.

Nice to have

  • Startup DNA: Startup experience preferred with proven comfort navigating ambiguity and high-velocity execution.

Skills

  • Define prompting standards, guardrails, and success metrics (accuracy, tone, safety, outcome quality).
  • Build lightweight evaluation frameworks that scale across clients.
  • Guide associates or EMs learning prompting and integration skills; contribute to playbooks, templates, and internal training.
  • Growth mindset focused on continuous skill development in rapidly evolving AI landscape

Compensation

  • Competitive salary including base + bonuses

Benefits

  • Comprehensive health coverage (medical, dental, vision) from day one
  • Generous PTO, company-wide R&R shutdowns, and paid parental leave
  • Retirement plan support for US and global employees

Company info

  • Balance speed vs. scalability; protect the platform from over-engineering while ensuring customers see real value quickly.
  • intensity to win, growth without limits, and a team that solves hard problems and celebrates big wins together
  • Learn more about us and meet our team here https://www.youtube.com/watch?v=VGYZ59n_x-c
  • Location and Work Environment
  • This role is 3 days a week (Tues - Thurs) minimum in office.
  • Candidates must be comfortable working with colleagues in different time zones (UK), and have valid travel documents without work authorization restrictions in the US.
  • Diversity and Inclusion
  • We are dedicated to creating a diverse and inclusive environment where everyone feels valued and supported.
  • We encourage applications from candidates of all backgrounds and offer accommodations upon request throughout the hiring process.
  • If you have any questions, please reach out to Allison Langille, Head of People, at jobs@valence.co.
  • Valence is committed to protecting the privacy of all applicants.
  • Information you submit will be used for recruiting, evaluation, legal compliance, and recordkeeping purposes only.
  • We do not require access to personal account credentials at any stage of the hiring process.

Visa & Work Authorization

  • Candidates must be comfortable working with colleagues in different time zones (UK), and have valid travel documents without work authorization restrictions in the US.

This listing is sourced directly from Valence's careers page and normalized into a canonical job model.