Applied AI Engineer, Life Sciences

About the Role

What You’ll Do

• Build production-grade applications using LLMs, retrieval, agents, structured data, and multimodal AI.
• Design AI workflows across pharmaceutical commercial, medical, and patient use cases.
• Build retrieval and knowledge systems over scientific, medical, and enterprise data.
• Develop evaluation frameworks for accuracy, reliability, safety, and domain-specific failure modes.
• Work with pharma datasets including CRM, claims, sales, HCP, patient, clinical, and scientific data.
• Prototype quickly, evaluate approaches rigorously, and productionize what works.
• Work directly with domain experts and customers to translate complex workflows into technical solutions

What We’re Looking For

• 3+ years of experience in AI/ML, applied machine learning, or software engineering.
• Strong Python skills and experience building production AI systems.
• Hands-on experience with LLMs, embeddings, retrieval, agentic workflows, or related applied AI systems.
• Prior experience working directly with pharmaceutical companies, pharma teams, or life sciences products.
• Strong fundamentals in experimentation, evaluation, and debugging AI systems.
• Excellent communication with technical and non-technical stakeholders.
• High ownership and comfort solving ambiguous problems.

Why This Role Matters

Strong Plus

• Pharma commercial, medical affairs, patient services, clinical, or market access experience.
• Experience with healthcare datasets, scientific literature, or medical knowledge systems.
• Experience with voice AI, speech systems, or regulated AI deployments