Embedded Data & AI Engineer (Foundry)

Novartis Group Companies; Cambridge (MA); Hybrid; USD 160,000 - 298,000; Full time

Job summary

The Novartis Group of Companies seeks a Forward Deployed Engineer (FDE) Data42 in Cambridge, MA. You will partner with domain teams to turn high-value problems into data and AI applications on Palantir Foundry, from prototype to production.

Responsibilities include building end-to-end data pipelines, ontology alignment, and user-facing workflows; collaborating with product managers, data scientists, and platform teams to deliver durable, repeatable analytics and software products.

Qualifications

• Bachelor's degree in Biology, Bioengineering, Bioinformatics, Biostatistics or related discipline.

Responsibilities

• Embedded delivery and problem solving: Embed with domain teams to understand workflows, define success criteria, and translate needs into shipped capabilities.
• Build on Palantir Foundry: Design and implement end-to-end solutions in Foundry, including data pipelines, ontology alignment, and application workflows.
• Data engineering and modeling: Ingest, transform, and model diverse datasets for analytics and applications.
• Application development and integration: Build user-facing applications or workflow experiences and ensure production readiness.
• Cross-functional leadership: Partner with product managers, data scientists, data engineers, governance, and platform teams.
• Enablement and reuse: Create reusable patterns and mentor teammates.

Skills

Strong programming skills

User empathy

Excellent communication

Stakeholder management

Rapid prototyping to production

Education

Bachelor's degree in Biology, Bioengineering, Bioinformatics, Biostatistics or related discipline

Tools

Palantir Foundry

Job description

The Novartis Group of Companies seeks a Forward Deployed Engineer (FDE) Data42 in Cambridge, MA. You will partner with domain teams to turn high-value problems into data and AI applications on Palantir Foundry, from prototype to production.

Responsibilities include building end-to-end data pipelines, ontology alignment, and user-facing workflows; collaborating with product managers, data scientists, and platform teams to deliver durable, repeatable analytics and software products.