Senior Sales Engineer (AI Data Solutions)
Posted Updated
Description
- The Sales Engineering team partners with Sales to deliver expert technical support for Komodo’s real-world data, AI-powered analytics, and software for our Life Sciences customers
- We act as trusted advisors — bridging data and AI expertise with commercial strategy to help clients solve their most pressing challenges and reduce the burden of disease
- The Senior 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
- 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
- What you’ll accomplish in your first 12 months:
- Become a go-to expert for Komodo’s AI-powered platform — routinely running live, plain-language analyses that compress weeks of work into minutes and shorten the path from discovery to close
- 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 — and share them so the whole team moves faster
- Confidently articulate Komodo’s trustworthy-AI approach — grounded, explainable, reproducible, verified, governed — to technical buyers, customer AI councils, and compliance/procurement stakeholders, clearing the AI-related blockers that stall deals
- Strengthen the Sales Engineering and Sales partnership through better discovery, qualification, and solution design — and surface cross-sell and expansion paths across the Komodo portfolio
- Build trusted client relationships by tying Komodo’s data and AI capabilities to clients’ commercial outcomes and ROI
- You are the kind of person who builds their own tools
- You turn one-off analyses into reusable assets, automate your own workflow, and have spent real time hands-on with AI — building or experimenting with agents, apps, and analytics co-pilots
- You don’t wait for enablement to hand you a script; you build the thing yourself
- 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
- Regulated-environment savvy. Experience navigating HIPAA, GDPR, and the compliance and AI-governance implications for life sciences clients
- Range as a communicator. You translate complex technical and AI concepts into clear, business-relevant insight, and connect equally well with executive and technical stakeholders
- 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). Experience with privacy-preserving linking is a plus
- Experience. 7+ 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 — demonstrated tinkering, resourcefulness, and a bias toward building are
- AI fluency. 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
- The ability to demo and quantify. Demonstrated success demoing and positioning AI-powered analytics products and connecting their capabilities to measurable customer ROI
- 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)