Valence

Solutions Engineer

• 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.

Solutions Engineer, AI

Revenue Operations

• Manage core revenue operations workflows, including campaign setup, list enrichment, and post campaign routing to Sales.
• Own our CRM, ensuring reporting grade data, clean workflows, and reliable GTM dashboards.
• Build and refine conversion funnel and attribution reporting to show which accounts, programs, and motions drive pipeline and revenue.
• Map target accounts and buying groups, and build net new lists in partnership with GrowthOps and Commercial leaders.
• Deploy AI tools to automate workflows, improve data hygiene, and surface insights that inform new GTM experiments.
• Develop repeatable processes and documentation that scale execution and enable tight cross-functional collaboration.
• Surface insights from marketing and sales data to inform new experiments and continuous optimization.

Associate, Revenue Operations

Recruitment

• Lead full-cycle recruiting for Sales, Customer Success, and GTM operations roles.
• Partner with GTM leadership to shape hiring strategy and create precise, high-signal evaluation processes.
• Source and engage candidates who understand enterprise AI, complex solution selling, and global customer workflows.
• Manage a rigorous, data-driven approach to pipeline health, time-to-hire, and quality-of-hire.
• Ensure every candidate has a clear, selective, high-touch experience aligned with Valence’s bar for excellence.

GTM Recruiter

Technical Recruiter

• Manage full-cycle recruiting across Product, Engineering, ML, and Design roles.
• Partner with technical leadership to define role profiles, scorecards, and high-precision evaluation loops.
• Build diverse candidate pipelines using advanced sourcing techniques and targeted outreach.
• Drive a fast, rigorous, signal-rich interview process for highly technical roles.
• Serve as a strategic advisor to hiring managers on market insights, org design considerations, and long-term talent planning.

Operations

• Manage GTM operations workflows - including list building, data enrichment, campaign execution, and reporting.
• Build and automate sophisticated contact and account segmentation for ABM, events, and digital campaigns.
• Deploy AI tools (like Clay) to orchestrate workflows, automate manual tasks, and drive smarter targeting and measurement.
• Track KPIs across channels (email, LinkedIn, website, events) to inform campaign performance and pipeline impact.
• Maintain Salesforce and HubSpot data hygiene to ensure accuracy, segmentation quality, and attribution clarity.
• Develop repeatable processes and documentation that scale execution and enable tight cross-functional collaboration.
• Implement campaign taxonomy and multi-touch attribution to illuminate what’s working.
• Surface insights from marketing and sales data to inform new experiments and continuous optimization.

Associate, Growth Operations

Engineer

• Own end-to-end customizations: Lead discovery → design → implementation → evaluation → iteration cycles for enterprise-grade workflows.
• 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.

Forward Deployed Engineer

• Lead enterprise customizations for Nadia—our AI coach—adapting and deploying tailored solutions for complex customer environments.
• Design, implement, and evaluate high-impact workflows (prompts, memory/knowledge patterns, coaching flows).
• Balance bespoke vs. reusable architectures, and build the tooling and evaluation muscle that helps us scale enterprise AI deployments.
• Collaborate cross-functionally with Product, AI Research/Applied AI, and Engineering, ensuring our most advanced enterprise AI systems are safe, performant, and aligned with user outcomes.
• Make hard tradeoffs: Balance speed vs. scalability; protect the platform from over-engineering while ensuring customers see real value quickly.
• Mentor and level up others: Guide associates or EMs learning prompting and integration skills; contribute to playbooks, templates, and internal training.
• Track deployment speed, adoption, satisfaction, and quality; identify opportunities for reusability and efficiency gains.

Solutions Architect, AI

Manager

• Build and grow strategic client partnerships, engaging across all levels of leadership including C-suite and executives
• Lead the consultative deployment of Valence's generative AI coaching tools within enterprise accounts, translating client goals into high-impact, scalable programs
• Deliver on strategic and commercial goals, meeting or exceeding revenue, usage, and expansion targets within your portfolio; own the renewal and expansion process
• Embed deeply within client organizations as a programmatic partner to unlock measurable value through clear use cases
• Champion behavior change by guiding clients through a consultative methodology and aligning the platform with their priorities
• Partner closely with Sales during pre-sale and pilot phases to shape solutions that convert interest into long-term engagement
• Oversee contracting and invoicing, working hand-in-hand with Operations to ensure a seamless experience
• Act as a client voice in product evolution, offering insights to shape the roadmap and improve the user experience
• Continuously build working fluency in generative AI, trust & ethics in ML, and the nuances of clients’ industries

Engagement Manager

Product Manager

• Act as GM for enterprise engagement, setting vision for enterprise adoption and retention at organizational scale
• Lead strategic product direction and roadmap development with product and technical leadership
• Own success metrics end-to-end, including activation, engagement, and long-term retention across large enterprise deployments
• Define, prioritize, and validate hypotheses via fast, data-driven experiments; craft programs to test, learn, and iterate quickly
• Lead discovery efforts: enterprise buyer journeys, process reviews, user interviews, and segmentation
• Translate Fortune 1000 customer complexity into scalable platform features, balancing customization with product cohesion
• Collaborate across engineering, design, and customer-facing teams to align enterprise processes, change management, and product execution
• Own and execute creative product marketing experiments, including messaging and AI-assisted approaches to drive enterprise adoption
• Lead product teardowns and retrospectives to surface lessons and uphold a high bar for product judgment and craft

Principal Product Manager, Enterprise

Chief of Staff

• Architect and optimize AI-powered talent systems end-to-end
• Lead workforce planning with Finance and develop data-driven headcount models
• Own searches for multiple high-impact roles and ensure timely hiring
• Design onboarding, performance enablement, and manager development systems
• Run fast pilots, A/B tests, and scale successful people systems
• Build talent intelligence engine with market benchmarking and predictive analytics
• Deliver executive-ready people analytics and partner on org design and culture projects
• Collaborate closely with VP of People & Operations and report outcomes to leadership

Chief of Staff, People and Talent

People Operations

• Architect and optimize AI-powered talent systems end-to-end using automation and analytics
• Lead dynamic workforce planning and partner with Finance on headcount models
• Own searches for multiple high-impact roles and ensure right talent timing
• Design onboarding journeys, performance enablement, and manager development systems
• Run fast pilots and A/B tests for people systems and workflows
• Build Valence’s talent intelligence engine and deliver predictive people analytics
• Partner with CEO and VP on org design and culture-shaping projects

People Strategy and Operations Manager

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.

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.

The Role
In this role you'll be be the founding GM-type product leader wholly accountable for end-to-end retention, user engagement, and activation for a critical product area. You'll own and define the full journey for enterprise end-users, from onboarding through ongoing engagement. This is not a feature shipper role - you’re building retention frameworks, defining and measuring user success, and pioneering hands-on, rapid experimentation at the intersection of AI and user experience. Expect to drive hypotheses, rapidly iterate in zero-to-one fashion, and immerse yourself with actual users to discover needs and fuel the next wave of enterprise value. In other words, you’ll ship to discover value, not only to deliver roadmap features.

Principal Product Manager, 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.
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.
This founding role will define how we deliver our AI coaching platform across the enterprise, driving organizational change that will touch millions of end users.
You'll be the architect of how Nadia, our AI coach, adapts to each company - customizing landing pages, coaching flows, response patterns, and specialized features.
Lead Fortune 500 deployments, partner with industry leaders, and advise C-level executives on AI transformation strategies.
Build the customization playbook, run technical discovery, gather requirements, and implement solutions through prompt engineering and variable configuration.
Work cross-functionally with Engineering and Customer Success to balance client needs with platform scalability and influence product evolution.
Gain direct exposure to advanced enterprise AI implementations and access to technologies before public release.