Solutions Engineer (Life Sciences)

TL;DR

Solutions Engineer (Life Sciences): Help F100 organizations realize the platform's potential through compelling demonstrations, proof-of-concepts, and technical strategies with an accent on drug discovery, clinical analytics, regulatory compliance, and data governance. Focus on designing tailored architectures, identifying novel use cases, building custom prototypes, and ensuring successful customer deployments.

Remote US

$114,000 base (US), OTE $174,000 USD

Company

hirify.global builds a platform that enables AI-driven organizations to develop, deploy, and operate data science and AI solutions at scale for customers like Johnson & Johnson and GSK.

What you will do

• Engage deeply with customer technical problems in life sciences workflows to propose optimal solutions.
• Design and execute hands-on proof-of-concept projects for use cases like model development for drug discovery and omics data processing.
• Collaborate with account executives to architect solutions addressing data governance, reproducibility, and validation requirements (e.g., 21 CFR Part 11).
• Identify novel use cases and build reusable technical assets to accelerate future engagements.
• Partner with Customer Success to transition POCs to production and develop custom prototypes using AI-assisted coding.

Requirements

• Technical background in life sciences (pharma, biotech, CRO, genomics, or medical devices) with code-first analytical or scientific work experience.
• Knowledge of at least one life sciences domain: drug discovery, clinical development, computational biology, manufacturing/QC, or regulatory data management.
• Experience owning or contributing to platforms or shared scientific computing environments.
• Background in solutions engineering, pre-sales, or customer-facing technical roles involving problem diagnosis and POCs.
• Production or near-production coding experience (internal tools, pipelines, applications) for scientific teams.
• Proficiency in Python and/or R; hands-on with data science and ML tools in life sciences.

Nice to have

• Familiarity with model building, validation, and productionization in regulated contexts.

Culture & Benefits

• Diverse, growth-minded team emphasizing truth-seeking, continuous improvement, and being your whole self.
• Equity, company bonus or sales commissions, 401(k), medical/dental/vision benefits, wellness stipends.
• Environment of teaching and learning to support success.