Head of AI Platform & Agentic Engineering

Merck; Cambridge (MA); Hybrid; USD 194,000 - 306,000; Full time

Benefits offered by this job

Medical, dental & vision insurance

401(k) plan

Paid holidays & vacation

Sick days & family leave

Bonus eligibility

Job summary

Merck & Co., Inc. in Cambridge, MA invites a Director to lead AI Platform & Agentic Engineering, accelerating target discovery with cutting-edge AI/ML methods. You will oversee a platform that connects multimodal data, models, and scalable compute, while collaborating with scientists.

This hands-on leadership role spans software, data engineering, and foundation models; you will mentor engineers and guide researchers in deploying AI approaches across biomedical projects.

Qualifications

• PhD or Master’s with significant industry experience in AI/ML or related field.

Responsibilities

• Build and evolve the AI/ML research environment, tooling, and reusable capabilities for scientists.
• Develop frameworks for AI agents, tool integration, retrieval, orchestration, and human‑in‑the‑loop workflows.
• Provide access to cloud, Databricks, GPU clusters, and HPC environments for AI research.
• Own SDLC for shared AI/ML tools, establish standards for architecture, testing, CI/CD, reproducibility, security, and maintainability.
• Mentor engineers and support scientists to translate new AI approaches into applications.

Skills

Python

AI/ML frameworks

Cloud computing

AWS

Databricks

Spark

Docker

Kubernetes

GitHub

CI/CD

LangGraph

Semantic Kernel

AutoGen

RAG pipelines

Knowledge graphs

Agentic AI

Communication

Education

PhD in Computer Science/Engineering/Data Science/AI/ML or related STEM field

Master's degree with 10+ years of industry experience

Tools

AWS

Databricks

Spark

Docker

Kubernetes

GitHub

CI/CD

Job description

Merck & Co., Inc. in Cambridge, MA invites a Director to lead AI Platform & Agentic Engineering, accelerating target discovery with cutting-edge AI/ML methods. You will oversee a platform that connects multimodal data, models, and scalable compute, while collaborating with scientists.

This hands-on leadership role spans software, data engineering, and foundation models; you will mentor engineers and guide researchers in deploying AI approaches across biomedical projects.