Senior Sales Engineer - Life Sciences

Responsibilities

• Partner with Sales during discovery to identify technical, data, and AI requirements, pain points, and desired commercial outcomes for life sciences clients.
• Provide expert guidance on healthcare claims and real-world data, including clinical ontologies, identity resolution, and patient-journey insights.
• Design and present tailored solutions that combine Komodo’s Healthcare Map, AI engine and software products to meet client objectives — and quantify the business value.
• Conduct technical and AI-powered demonstrations — including live, plain-language analyses and no-code exploration — that show how clients can better target, engage, and convert healthcare providers and patients.
• Position how Komodo’s differentiated AI aligns with foundational, general-purpose models and other real-world-data vendors, addressing model trust, data provenance, reproducibility, and governance.
• Support customer AI councils, security reviews, and enterprise procurement to unlock and accelerate larger, multi-product deals.
• Identify and shape expansion opportunities across Komodo’s products to grow account revenue.
• Navigate the internal review process for technical proposals, ensuring alignment with Legal, Compliance, Security / AI Governance, and Product teams.
• Collaborate with cross-functional teams so customer and competitive feedback influences the product and AI roadmap.
• Provide technical and AI mentorship to junior SEs, sharing best practices and reusable assets for supporting life sciences clients.

Requirements

• Deep familiarity with large BioPharma functional areas (e.g., Commercial, HEOR/RWE, Medical Affairs) and their core processes and workflows, with a demonstrated track record of driving material improvements within them.
• 7+ years of experience in Sales Engineering, Solutions Engineering, or Technical Account Management, with a strong emphasis on selling software, real-world data, and analytics to life sciences / pharmaceutical companies.
• Proven success partnering with Sales to support discovery, qualification, and solution design that drives revenue.
• Deep understanding of healthcare claims and real-world data (e.g., 837/835 data, NDC codes, clinical ontologies) and life sciences commercial strategies.
• Working fluency with AI/ML concepts relevant to enterprise analytics — LLMs, generative and agentic AI, and retrieval-grounded analytics — and the ability to explain AI trust, reproducibility, and governance to technical and non-technical buyers.

Nice-to-Haves

• Experience building repeatable, AI-centric demo assets and proof-of-value frameworks.
• Experience supporting customer AI councils, security reviews, and enterprise procurement processes.