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Role Description

This role owns a portfolio of the company’s most strategic customers—many of whom are technical AI teams—ensuring projects launch smoothly, deliver measurable outcomes, and expand into long-term partnerships. You’ll sit at the intersection of customer success, program delivery, and product influence, partnering closely with Engineering, Data, Product, and Leadership.

• Own high-stakes customer programs
• Lead end-to-end delivery for complex, multi-workstream engagements—from kickoff through final readout and ongoing expansion.
• Translate ambiguous customer needs into clear scopes, milestones, success metrics, and deliverables.
• Run cross-functional execution (and jump in when needed)
• Coordinate internal teams (Product, Data, Engineering, Operations) to hit timelines and quality bars.
• Unblock execution, surface risks early, and drive resolution—occasionally getting hands-on with artifacts like analysis plans, evaluation summaries, or workflow specs.
• Be the primary customer interface
• Manage executive-level relationships and day-to-day stakeholders.
• Set communication cadence, run steering check-ins, handle escalations, and ensure crisp alignment.
• Convert insights into product leverage
• Synthesize customer feedback into scalable improvements: repeatable processes, templates, playbooks, and product roadmap inputs.
• Partner with Product to shape what becomes “standard” vs. bespoke.
• Drive retention and growth
• Own renewal readiness, account health, and expansion opportunities.
• Identify upsell paths tied to value (new datasets, evaluation modules, workflow automation, added sites/teams, etc.).

Qualifications

• 6+ years in a client-facing role: customer success, strategic account management, solutions consulting, engagement management, or similar.
• Demonstrated strength in program/project management across cross-functional technical teams.
• Comfort working with complex data products (structured + unstructured; bonus for imaging, time-series, waveforms, or multimodal pipelines).
• Ability to bridge technical and non-technical conversations—credible with ML/engineering and effective with senior executives.
• Track record of driving retention and expansion (renewals, upsell, multi-year partnerships, or growth in account scope).
• Highly organized, proactive, and effective in fast-moving, build-as-you-go environments.

Requirements

• Experience in regulated AI (healthcare, life sciences, fintech, insurance, public sector, etc.).
• Familiarity with evaluation/validation concepts (model performance studies, monitoring, data quality frameworks, evidence generation).
• Exposure to regulatory, compliance, or procurement considerations that influence adoption.
• Prior work supporting consortium-style initiatives, research collaborations, or multi-stakeholder programs.

Benefits

• Competitive base + performance upside + equity (details shared in process), plus comprehensive benefits.