• Expand strategic accounts: Build deep relationships with stakeholders across analytical development, quality control, and R&D informatics to uncover growth and cross‑sell opportunities. • Drive new enterprise sales through a consultative sales approach: Identify, target, and win new business with leading biopharma organizations looking to digitalize MS‑based analytical workflows, developing compelling proposals, and mutual success place that clearly demonstrate the impact and value of Genedata Expressionist • Lead and own complex sales engagements: Orchestrate enterprise‑level deals involving scientific, IT, and business stakeholders, managing the full sales cycle from lead generation and qualification through solution development, negotiation, closing and post-sale account expansion. • Collaborate cross‑functionally: Partner closely with scientific consultants, project managers, legal, marketing, and development teams to deliver tailored enterprise solutions and seamless transitions to implementation. • Represent Genedata in the market and bring the customer voice internally: Act as a brand ambassador at conferences, industry events, and customer meetings through impactful presentations and networking. Capture and relay customer feedback to help shape product strategy and future innovation.

• Own all Engineering and Data recruiting end-to-end: intake through close. • Directly manage and develop a Senior Recruiter while maintaining your own requisition load. • Build and execute talent strategies for Engineering and Data. • Serve as the primary recruiting partner to Engineering and Data leadership. • Use funnel data and hiring outcome metrics to diagnose recruiting challenges.

• Own and define end-to-end program management for the 50+ members of the Productivity Engineering team • Drive complex cross-team programs such as large-scale platform migrations and tooling adoptions across multi-quarter timelines • Define success through developer adoption and productivity impact • Manage migrations as a program • Drive AI developer tooling strategy and adoption • Own the Platform Engineering team's Roadmap and OKR planning cycles

• Own and define end-to-end program management for the 50+ members of the Productivity Engineering team. • Drive complex cross-team programs such as large-scale platform migrations. • Define success through developer adoption and productivity impact. • Manage migrations as a program: develop playbooks and track progress. • Drive AI developer tooling strategy and adoption. • Own the Platform Engineering team's Roadmap and OKR planning cycles.