Director, Engineering

Team: Engineering

Location: Palo Alto, CA

Commitment: Full Time

Workplace Type: onsite

Responsibilities

• Translate high-level vision into concrete, actionable engineering roadmaps, driving a high-tempo shipping cadence and ensuring the team consistently hits critical product and infrastructure milestones on strict timelines.

• Actively contribute to the codebase as a hands-on engineering leader, writing code, reviewing pull requests, and setting the technical bar while coordinating complex efforts across diverse product and infrastructure teams.

• Build the critical operational bridge between research and engineering, architecting solutions to transition cutting-edge, experimental foundation models into robust, scalable, and highly available production systems.

• Instill a relentless culture of rigor, velocity, and code quality by defining and enforcing uncompromising standards for automated testing, CI/CD pipelines, and optimal developer experience.

• Actively manage, mentor, and level up both junior and senior engineers, providing hands-on coaching, performance feedback loops, and architectural guidance to maximize their growth and technical output.

• Partner closely with the executive leadership team and AI research leads to proactively identify critical path dependencies, clear blockers, and align technical execution with the company’s ambitious scientific and commercial goals.

Qualifications

• Extensive engineering experience (10+ years), with at least 5 years in senior leadership roles, demonstrating a proven track record of managing managers, scaling high-performing teams, and maintaining hands-on technical proficiency.

• Exceptional technical expertise in modern AI infrastructure, with deep, hands-on experience building, scaling, and deploying complex generative AI products and massive foundation models into production environments.

• Demonstrated execution-oriented mindset with the ability to swiftly transition complex, ambiguous technologies from a conceptual R&D phase into a highly reliable, commercial-grade enterprise platform.

• Deep architectural understanding of high-performance computing, strategic GPU cluster optimization, and the unique distributed systems challenges involved in training and serving foundation models at scale.

• Outstanding cross-functional orchestration skills, with the ability to manage complex project timelines and keep diverse, fast-moving teams focused on critical deliverables.

Preferred Qualifications

• Domain knowledge or prior experience working within computational biology, genomics, drug discovery, or integrating AI into scientific software platforms.

• Familiarity with building robust internal developer platforms, complex MLOps pipelines, or unified frameworks (similar to our AIDO Foundry) to accelerate AI deployment.

• Prior experience at an early-stage, hyper-growth AI startup, demonstrating the ability to thrive in a highly ambiguous and fast-paced environment.