Enterprise Account Executive (Healthcare & Life Sciences)

The Enterprise Account Executive (Healthcare & Life Sciences) will report to the Director of Enterprise GTM and own revenue growth across a portfolio of Scale AI’s most strategic healthcare and life sciences customers. This role is focused on selling complex, agentic AI solutions - autonomous workflows powered by LLMs and human-in-the-loop systems - into health systems, payers, pharma, biotech, and digital health organizations.

You will act as a strategic partner to clinical, operational, and technical leaders - helping them transform core workflows such as clinical documentation, prior authorization, revenue cycle, pharmacovigilance, clinical trials, medical affairs, and patient engagement through AI agents. This is a highly consultative, technical enterprise sales role requiring deep domain fluency, strong executive presence, and the ability to navigate regulatory, compliance, and multi-stakeholder complexity.

You will own the full customer lifecycle - from origination through close, deployment, and expansion - while quarterbacking cross-functional teams across Solutions Engineering, Product, Research, and Delivery to land and scale high-impact AI programs.

You Will:

• Own and expand relationships with leading healthcare and life sciences organizations (providers, payers, pharma, biotech), focusing on multi-year, strategic AI initiatives
• Sell agentic AI solutions by mapping Scale’s capabilities to high-impact workflows (e.g., clinical documentation, prior auth, revenue cycle, patient ops, clinical trials, drug safety, medical review)
• Build trusted relationships with executive stakeholders (CIO, CTO, CMIO, Chief Data/AI Officer, Heads of Clinical Ops, R&D, Commercial)
• Develop and execute multi-threaded account strategies that drive net-new revenue, expansion, and long-term platform adoption
• Lead complex deal cycles, including ROI modeling, business case development, and mutual close plans across new business, renewals, and expansions
• Partner closely with Solutions Engineering to design and land technically credible pilots, POVs, and production deployments
• Navigate healthcare-specific regulatory and compliance requirements (e.g., HIPAA, GxP, data governance, auditability) throughout the sales process
• Act as the voice of the customer internally - informing product roadmap, agent design, and vertical-specific solutions
• Maintain strong pipeline discipline, forecasting accuracy, and deal hygiene using Salesforce, Clari, and related tools
• Operate effectively in a fast-paced, cross-functional environment with high ownership and attention to detail

Ideally, You Will Have:

• 8–12+ years of enterprise sales experience, with significant focus on healthcare or life sciences (providers, payers, pharma, biotech, or digital health)
• Proven track record of closing and expanding large, complex, multi-million dollar deals in regulated environments
• Experience selling AI/ML, data platforms, or workflow automation technologies, with the ability to position agentic / LLM-driven solutions to both technical and non-technical stakeholders
• Strong understanding of key healthcare/life sciences workflows (e.g., clinical operations, revenue cycle, patient engagement, R&D, clinical trials, pharmacovigilance)
• Demonstrated success engaging executive stakeholders and building compelling ROI-driven business cases
• Familiarity with regulatory and compliance considerations (e.g., HIPAA, FDA/GxP, data privacy, model governance)
• Strong command of enterprise sales fundamentals, including account planning, multi-threading, and forecasting discipline
• Ability to navigate long, complex sales cycles with multiple stakeholders and competing priorities
• Excellent communication, storytelling, and executive presence
• High degree of ownership, intellectual curiosity, and a consultative, customer-first mindset

Nice to Haves:

• Experience selling agentic AI, LLM platforms, or automation solutions into healthcare or life sciences
• Background working with clinical, regulatory, or data organizations
• Familiarity with EHR systems, clinical data, or real-world evidence platforms
• Experience in high-growth or emerging t