Senior Director, Agentic AI and Automation

Madrigal is a biopharmaceutical company focused on delivering novel therapeutics for metabolic dysfunction-associated steatohepatitis (MASH), a liver disease with high unmet medical need. Madrigal’s medication, Rezdiffra (resmetirom), is a once-daily, oral, liver-directed THR-β agonist designed to target key underlying causes of MASH. Rezdiffra is the first and only medication approved by both the FDA and European Commission for the treatment of MASH with moderate to advanced fibrosis (F2 to F3). An ongoing Phase 3 outcomes trial is evaluating Rezdiffra for the treatment of compensated MASH cirrhosis (F4c).

Job Title

Senior Director, Agentic AI & Automation

Department & Manager

Department: IT
Manager: Executive Director, AI and Data Science

Job Profile Summary

Madrigal Pharmaceuticals is seeking an innovative, systems‑thinking leader to set the vision, design, and enterprise‑wide deployment of agentic workflows—AI‑enabled, plan–act–reflect automations that learn over time and augment human decision‑making. You will orchestrate autonomous or semi‑autonomous digital agents across R&D, Commercial, Medical Affairs, and Corporate functions, accelerating operational efficiency and unlocking the full potential of generative and agentic AI within a regulated biotech environment.

Role & Responsibility

• Define and execute a multi‑year agentic AI & RPA roadmap converging hyperautomation, process‑mining, and LLM‑driven workflows.
• Operationalize an Agentic Automation Center of Excellence (CoE) governing standards, reusable assets, and ROI tracking.
• Partner with cross‑functional executives to prioritise high‑value automations across the business.
• Champion MCP and agent‑orchestration patterns for future‑proof integration.
• Architect modular multi‑agent systems powered by frontier LLMs and leading agent frameworks (LangChain family, AutoGen, CrewAI, etc.).
• Design secure agent‑to‑agent (A2A) communication with shared memory, credential vaults, RBAC.
• Implement enterprise MCP engine and Agent Protocol standards enabling human–agent–bot collaboration.
• Standardise integration with vector stores and cloud MLOps platforms (Azure AI Search, Databricks, SageMaker, Vertex AI).
• Build event‑driven, low‑code pipelines (n8n, Dify, Glean) to trigger agentic RPA tasks in real time.
• Implement observability and governance (Arcade.dev, AgentOps, Langfuse).
• Establish robust testing harnesses and GxP‑compliant validation for every autonomous workflow.
• Leverage process‑ & task‑mining insights to auto‑generate automation backlogs and measure value.
• Lead a multi‑disciplinary squad of AI automation architects, prompt engineers, and product managers to drive iterative product delivery using agile OKRs, rapid POCs, and continual KPI evaluation.
• Experiment with cutting‑edge agent research (ReWOO, SuperAGI, CAMEL) and open‑source Agentic RPA.
• Collaborate with open‑source communities, cloud partners, and leading vendors.
• Set standards for agent safety, ethical AI, and closed‑loop feedback.
• Forge deep partnerships with Enterprise Data, IT Infrastructure, and Cybersecurity teams.

Qualifications

• Advanced degree (Ph.D. preferred) in AI, Data Science, Computer Science, Applied Mathematics, Engineering, Physics, or related field.
• 15+ years leading AI/ML or intelligent‑automation initiatives; 10+ years hands‑on with Python, SQL, R, MATLAB, PyTorch, Keras, Git.
• 12+ years architecting ML/deep‑learning solutions incl. LLMs (GPT‑4, BERT, LLaMA, Dolly) and RAG pipelines.
• 8+ years building web apps (Dash, Streamlit, Shiny) and advanced data products.
• 8+ years implementing scalable AI/ML on platforms like Databricks or Dataiku, with strong AI/MLOps.
• Deep knowledge of cloud data platforms (AWS, Azure, GCP) and compliance (GxP, HIPAA, GDPR).
• Strong theoretical foundation in ML/AI with contributions to papers and presentations.
• Exceptional written & verbal communication skills translating complex research to executives.

Leadership/Autonomy

Leads multi‑disciplinary squads and influences enterprise‑wide AI & automation strategy. Operates with significant autonomy to set technical direction and allocate resources.

Problem Solving

Applies deep expertise in ML, generative AI, and systems engineering to solve complex, cross‑domain challenges. Leverages quantitative skills to inform data‑driven decisions and optimize agentic workflows.

Impact

Accelerates operational efficiency, compliance, and patient outcomes by embedding intelligent automation across critical functions. Establishes Madrigal as a leader in safe, regulated agentic AI deployment.

Typical Degree & Years of Experience

Ph.D. in a quantitative field plus 15+ years in AI/ML and in