Head of Platform Engineering

Head of Platform Engineering

Location: San Mateo, CA or NYC

About the Team

Genesis Molecular AI is at the frontier of applying large-scale AI to drug discovery. We are building AI systems that operate at the intersection of machine learning, chemistry, and biology, with the goal of enabling real breakthroughs in medicine.

Our teams are mission-driven, deeply technical, and motivated by the opportunity to work on problems that matter. This is not incremental work. We are defining what the “machine” looks like: the models, the data, the infrastructure, and the workflows that allow science and AI to meet in meaningful ways. Impact comes from ownership, curiosity, and a willingness to engage directly with hard, unsolved problems.

The Platform Engineering team builds and operates the infrastructure that underpins everything we do, from large-scale data ingestion and storage, to distributed model training, evaluation, and production inference.

About the Role
We are looking for a Head of Platform Engineering to lead our infrastructure and enable the next generation of AI-driven drug discovery. In this role you will lead this function end to end.

This is a senior leadership role for someone who enjoys working close to the systems themselves. You will be responsible not only for the technical architecture, but for how the platform earns trust, adoption, and impact across the organization.

While this is a leadership role, it is also a hands-on role. At Genesis, credibility comes from understanding the work deeply. You should expect to engage directly with the codebase, technical designs, and architectural decisions.

This role sits at the intersection of cutting-edge AI, large-scale systems, and real-world scientific impact. If you’re excited by building reliable platforms for training and deploying SOTA AI models, and want to work on AI that is genuinely good for humanity, this is a unique opportunity.

• Lead, mentor, and grow a high-impact platform engineering team, setting technical standards and fostering strong engineering culture.

• Partner closely with ML research, product leaders, and computational chemist teams to ensure the platform meets real user needs and evolves with the science.

• Own the end-to-end platform and infrastructure strategy supporting data, training, and large-scale inference.

• Design, build, and operate systems for large-scale AI workloads, with strong judgment around build vs. buy decisions.

• Stay hands-on when needed, with the ability to review code, provide technical feedback, and steer architectural direction.

• Navigate full lifecycle of AI infrastructure complexity including: data ingestion and storage, distributed training, evaluation, and production inference.

• Bring clear technical judgment to ambiguous problems, balancing input from others with the responsibility to make decisions that move the work forward.

• You have 8+ years experience leading teams of directs and indirects in fast-moving environments, with a startup mindset, and enjoy building alongside others, not just managing from a distance..

• You have experience designing and operating infrastructure for AI training and inference at scale.

• You bring strong systems thinking and the ability to reason about tradeoffs across performance, cost, reliability, and development velocity.

• Regardless of your years in leadership, you value engineering craftsmanship. You can, and like to code. This may show up through hands-on leadership, side projects, open-source contributions, or other signals of sustained technical curiosity. Show us your github :-)

• You are comfortable operating across abstraction layers, from cloud and hardware considerations to ML platforms and developer tooling.

• You have experience navigating organizational complexity. You have insightful, concrete stories about how you’ve managed conflicts, dependencies, and tradeoffs in real systems.

• Prior experience in AI for biology or drug discovery is not required, but curiosity and willingness to learn are essential.

If this sounds interesting, please reach out, we’d love to talk!

About Genesis Molecular AI

Genesis Molecular AI is pioneering foundation models for molecular AI to unlock a new era of drug design and development. The company’s generative and predictive AI platform, GEMS (Genesis Exploration of Molecular Space), integrates AI and physics into industry-leading models to generate and optimize drug molecules, including the breakthrough generative diffusion model Pearl for structure prediction. Genesis has raised over $300 million from leading AI, tech and life science-focused investors, signed multiple AI-focused research collaborations with major pharma partners, and is deploying GEMS to advance an internal therapeutics pipeline for a variety of high-impact targets.

Genesis is headquartered in San Mateo, CA, with a fully integrated laboratory in San Diego. We are proud to be an inclusive workplace and an Equal Opportunity Employer.