Principal Sales Engineer, AI Data Solutions

Komodo Health is a healthcare data and analytics company focused on reducing the global burden of disease through its Healthcare Map and AI-powered software. The Principal Sales Engineer, AI Data Solutions, provides technical, data, and AI expertise throughout the sales cycle, designing solutions and demonstrations for life sciences customers. The role also supports enterprise evaluations, develops reusable AI assets, mentors junior sales engineers, and connects product capabilities to customer outcomes and ROI.

Responsibilities:

• Partner with Sales during discovery to identify the 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 — clinical ontologies, identity resolution, 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
• Run technical and AI-powered demonstrations — live, plain-language analyses and no-code exploration — and handle the off-script, ad-hoc question with a real answer in the room rather than "we'll get back to you."
• Position how Komodo's differentiated AI compares to general-purpose foundation 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 — aligning Legal, Compliance, Security / AI Governance, and Product
• Feed customer and competitive signal back into the product and AI roadmap
• Mentor junior SEs and share reusable, AI-centric best practices and assets

Requirements:

• Deep familiarity with large BioPharma functional areas (e.g., Commercial, HEOR/RWE, Medical Affairs), their workflows, and how each thinks about data and budget — with a track record of driving material improvements within them
• 10+ years in Sales Engineering, Solutions Engineering, or Technical Account Management, selling software, real-world data, and analytics to life sciences / pharmaceutical companies
• You create your own assets and tools and have hands-on experience building or experimenting with AI agents and applications (e.g., Claude Code, Cursor, LangFlow, data-science notebooks). Production deployments are not required — demonstrated tinkering, resourcefulness, and a bias toward building are
• Working fluency with the AI/ML concepts relevant to enterprise analytics — LLMs, generative and agentic AI, retrieval-grounded analytics — and the ability to explain AI trust, reproducibility, and governance to both technical and non-technical buyers
• Deep understanding of healthcare claims and real-world data (e.g., 837/835 data, NDC codes, clinical ontologies); working SQL and Python; APIs, data integration, and cloud architectures (AWS, Azure)
• Demonstrated success demoing and positioning AI-powered analytics products and connecting their capabilities to measurable customer ROI
• You translate complex technical and AI concepts into clear, business-relevant insight, and connect equally well with executive and technical stakeholders
• Experience navigating HIPAA, GDPR, and the compliance and AI-governance implications for life sciences clients
• Experience with privacy-preserving linking is a plus
• Familiarity with responsible-AI / AI-governance frameworks and how they apply to healthcare and pharma procurement and AI council reviews
• Prior experience supporting customer AI councils or enterprise AI evaluations
• Technical certifications in AWS, Azure, or data platforms
• Experience with CRM platforms like Salesforce to manage client interactions and pipeline
• Familiarity with data visualization tools (e.g., Tableau, Looker)