Applied AI Engineer, Life Sciences

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

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.

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