Madrigal Pharmaceuticals is advancing transformational therapies with scientific rigor and a commitment to patients. Within Medical Affairs, we turn scientific evidence - publications, real-world evidence (RWE), HEOR, and field-medical insight - into decisions that advance patient care, and we operate a growing AI platform with multiple production agents supporting that work. We are seeking a Senior Manager, AI and Data Science who brings strong technical depth, hands-on experience with agentic AI, and an ownership mindset. This individual will own modular, high-impact workstreams end-to-end, from design through production - combining agentic AI and large language model (LLM) engineering with applied machine learning on real-world evidence - working alongside the platform's architect and Medical Affairs stakeholders.
We welcome candidates from a range of scientific, medical, and engineering backgrounds. What unites strong applicants is rigor and an evidence-driven approach to building and evaluating AI systems, an ownership mindset, and the ability to collaborate across scientific, technical, and business teams. The ideal candidate is comfortable owning ambiguous problems end-to-end.
Key ResponsibilitiesAgentic AI Systems
- Build and operate production AI agents and orchestration workflows using modern agentic frameworks such as LangGraph and deepagents.
- Design modular, reusable components for reasoning, retrieval, tool integration (including MCP), and workflow automation.
- Partner with the Agentic UI team to deliver seamless, end-to-end products.
Retrieval, RAG & Evaluation
- Own and optimize the retrieval stack, including vector and hybrid search, embeddings, chunking, and reranking.
- Build evaluation and regression safeguards for LLM outputs, with particular attention to citation faithfulness and groundedness, which are essential in Medical Affairs.
Applied Machine Learning on Real-World Evidence
- Design and deploy machine learning on real-world evidence (claims, EHR, registry), HEOR, and field-medical data to surface Medical Affairs insights.
- Apply embeddings, predictive models, and statistical methods where they are the right fit for the problem.
Data Integration & MLOps
- Automate and scale data-ingestion pipelines into AI/ML-ready data on platforms such as Databricks
- Own deployment, monitoring, and observability (for example, using LangSmith) for the systems you ship.
Cross-Functional Engagement & Governance
- Translate complex AI concepts into clear, actionable insights for technical and non-technical Medical Affairs partners.
- Align AI initiatives with enterprise governance, privacy, and PHI and compliance expectations.
Qualifications Required
- A demonstrated record of scientific rigor: either a Ph.D. in a quantitative or medical-adjacent field with first-author publications, or a strong engineering background paired with peer-reviewed research at top venues (for example, NeurIPS, ICML, ICLR, or ML4H). The specific credential matters less than the demonstrated rigor and record of shipping.
- 7+ years of applied machine learning or data science, including 3+ years shipping ML or AI systems to production.
- 1+ year of hands-on agentic AI development using modern frameworks (for example, LangGraph, deepagents, or LangSmith).
- Strong RAG and retrieval engineering, including vector and hybrid search, embeddings, and reranking, with the ability to evaluate groundedness and citation accuracy.
- Applied ML on real-world or patient-level data (claims, EHR, registry), including feature engineering.
- Experience with production reliability, data access and authentication, and handling sensitive (PHI) data.
- Strong communication skills and the ability to collaborate across scientific, technical, and business teams.
- Experience in Healthcare or Life Sciences.
Preferred
- Production experience with deepagents, LangGraph, and LangSmith; MCP tools; Azure; and Databricks Unity Catalog, Microsoft Fabric, or OneLake.
- Proven track record of deploying agents to production at scale, including LLM evaluation and observability.
- Background in real-world evidence, epidemiology, or HEOR analytics.
- Medical Affairs experience.
Madrigal's Total Rewards strategy is based on a biotech industry peer group comparator and is inclusive of base pay, bonus and equity. Our equity offers meaningful opportunity allowing our employees to share in the success they help create. By aligning individual and company performance, we empower employees to think like owners, giving them a stake in the organization.
All employees receive equity, which we believe reinforces our ownership culture. Base salary is determined by several factors including the candidate's qualifications, skills, education, experience, business needs and market demands. As of the date of this posting, a good faith estimate of the current pay scale for this position, applicable to all candidates, is $163,000 - $200,000 per year. We comply with all applicable minimum wage laws.
All full-time employees receive equity, which reinforces our ownership culture and offers meaningful opportunity for our employees to share in the success they help create. By aligning individual and company performance, we empower employees to think like owners, giving them a stake in the organization.
Full-time employees are also eligible for comprehensive benefits, including flexible paid time off, medical, dental, vision and life/disability insurance, and 401(k) offerings (i.e., traditional, Roth, and employer match) in accordance with applicable plans. We also offer additional voluntary benefits like supplemental life insurance, legal services, and other offerings. In addition, we offer mental health benefits through our Employee Assistance Program for employees and their family. The company also provides other benefits in accordance with applicable federal, state, and local laws.
