Senior Director, Agentic AI and Automation
Listed on 2026-10-14
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Software Development
AI Engineer (Applied/Software), Machine Learning/ ML Engineer
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).
Senior Director, Agentic AI & Automation
Department & ManagerDepartment: IT
Manager:
Executive Director, AI and Data Science
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 (Lang Chain family, Auto Gen, 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, Sage Maker, 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, Agent Ops, 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.
- 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…
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