Director, AI Platform & Agentic Engineering, AI & Genome Sciences

Job Description

AI/ML is central to our mission to accelerate target and biomarker discovery through a deeper understanding of disease biology.

We are seeking a Director, AI Platform & Agentic Engineering to build and lead the technical capabilities that allow scientists to rapidly develop, evaluate, and apply cutting-edge AI/ML methods. You will work across unique assets, including genome-scale perturbation data, proprietary foundation models, large-scale biological datasets, and experimental partnerships that enable model predictions to be tested in the lab.

This hands-on technical leadership role spans software and data engineering, scientific computing, foundation models, and agentic AI. You will build an agile research platform connecting multimodal data, knowledge graphs, scalable compute, and reusable AI tools to accelerate experimentation, reproducible research, and scientific discovery.

Primary Responsibilities:

• AI Platform & Research Engineering: Build and evolve the AI/ML research environment, developer tooling, and reusable capabilities that connect scientists with data, knowledge, compute, and models.
• Foundation Models & Agentic AI: Enable foundation model training, fine-tuning, and evaluation, and develop frameworks for AI agents, tool integration, retrieval, orchestration, and human-in-the-loop scientific workflows.
• Scientific Computing: Partner with IT and technology teams to provide flexible access to cloud, Databricks, GPU clusters, and other high-performance computing environments required for cutting-edge AI research.
• Agile Engineering: Own the SDLC for shared AI/ML tools and applications, establishing pragmatic standards for software architecture, testing, CI/CD, reproducibility, security, and maintainability to enable machine learning and data scientists.
• Technical Leadership: Remain actively engaged in architecture, prototyping, and implementation while mentoring engineers and supporting scientists in rapidly translating new AI approaches into scientific applications.

Required Qualifications:

• PhD in a relevant field such as Computer Science, Electrical Engineering, Data Science, Physics, Informatics, AI/ML, Mathematics, or a related STEM discipline, with 6+ years of industry experience, or Master's Degree with 10+ years of industry experience.
• Experience building AI/ML infrastructure, scientific software, or high-performance computing environments.
• Experience with cloud and computing technologies such as AWS, Databricks, Spark, Docker, Kubernetes, GitHub, and CI/CD.
• Strong software engineering expertise, particularly in Python, AI/ML frameworks, and modern software architecture.
• Experience developing GenAI and agentic AI systems, including frameworks such as LangGraph, Semantic Kernel, AutoGen, or equivalent.
• Experience with RAG, vector databases, knowledge graphs, and agent orchestration.
• Strong communication skills and ability to work effectively across scientific, engineering, and technology teams.

Preferred Qualifications:

• Advanced degree in Computer Science, Engineering, Machine Learning, Physics, or a related quantitative field, with significant industry experience.
• Hands-on experience with foundation model training, fine-tuning, and evaluation.
• Experience developing computational capabilities for biological or biomedical research.
• Experience creating internal scientific platforms, developer tools, or open-source software.

#EligibleforERP

Required Skills:

Agentic AI, Agile Engineering, Artificial Intelligence (AI), Computing Software, Data Engineering, Data Modeling, Data Science, Data Visualization, Deep Learning, Foundation Models, High Performance Computing (HPC), Kubernetes, Machine Learning (ML), Python (Programming Language), RAG Pipeline, Software Development, Software Engineering, Technical Leadership, Transformers Design

Preferred Skills:

Life Science, Omics

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