Principal Sales Engineer, AI Data Solutions

The Sales Engineering team partners with Sales to deliver expert technical support for Komodo's real-world data, AI-powered analytics, and software for Life Sciences customers. The Principal AI Sales Engineer provides technical, data, and AI-solution expertise across the discovery, qualification, value-alignment, and solution-design stages of the sales cycle. The through-line of the role is simple: help life sciences clients see a transformed workflow — analyses that used to take weeks, run live in minutes — and connect that directly to their commercial outcomes.

Responsibilities

Become a go-to expert for Komodo's AI-powered platform; Develop deep fluency in Komodo's Healthcare Map and real-world data assets, and in how our analytics and AI products solve specific customer pain points; Build a personal library of reusable AI-centric demo assets and proof-of-value frameworks; Confidently articulate Komodo's trustworthy-AI approach to technical buyers, customer AI councils, and compliance/procurement stakeholders; Strengthen the Sales Engineering and Sales partnership through better discovery, qualification, and solution design; Build trusted client relationships by tying Komodo's data and AI capabilities to clients' commercial outcomes and ROI; Partner with Sales during discovery to identify technical, data, and AI requirements, pain points, and desired commercial outcomes; 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; Run technical and AI-powered demonstrations; Position how Komodo's differentiated AI compares to general-purpose foundation models and other real-world-data vendors; Support customer AI councils, security reviews, and enterprise procurement; Identify and shape expansion opportunities across Komodo's products; Navigate the internal review process for technical proposals; Feed customer and competitive signal back into the product and AI roadmap; Mentor junior SEs and share reusable AI-centric best practices.

Requirements

Domain depth: 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; Experience: 10+ years in Sales Engineering, Solutions Engineering, or Technical Account Management, selling software, real-world data, and analytics to life sciences / pharmaceutical companies; A builder mentality: 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; AI fluency: Working fluency with 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; A strong data foundation: 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); Ability to demo and quantify: Demonstrated success demoing and positioning AI-powered analytics products and connecting their capabilities to measurable customer ROI; Range as a communicator: Translate complex technical and AI concepts into clear, business-relevant insight, and connect equally well with executive and technical stakeholders; Regulated-environment savvy: Experience navigating HIPAA, GDPR, and the compliance and AI-governance implications for life sciences clients.

Nice to have

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)

Benefits

Comprehensive health, dental, and vision insurance; Flexible time off and holidays; 401(k) with company match; Disability insurance and life insurance; Leaves of absence; Commissions; Eligibility for equity awards