Strategic Projects Lead - Engineering (Life Sciences & Chemical)

present of AI; San Francisco (CA); On-site; USD 140,000 - 210,000; Full time

Job summary

Present of AI in San Francisco seeks a Strategic Projects Lead - Engineering to drive complex life sciences and chemical projects at the intersection of engineering and AI. You will coordinate expert contributors across disciplines, design data specs, and guide projects from scoping through delivery with minimal direction.

You should break down unfamiliar engineering problems, communicate clearly, and thrive in ambiguous situations while building practical AI-enabled solutions for lab clients.

Qualifications

• Engineering background with ability to break down complex problems.
• Experience coordinating expert contributors across technical fields.
• Ability to scope and deliver projects with minimal direction.
• Strong communication and leadership in ambiguous environments.

Responsibilities

• Run projects with AI lab clients and coordinate expert contributors across technical fields.
• Carry projects from scoping to delivery with little direction.

Skills

Project management

Leadership

Python

Automation

Tools

CAD

Simulation

Hardware

Job description

Strategic Projects Lead - Engineering (Life Sciences & Chemical)

The role asks for someone with an engineering background who can run projects with AI lab clients and coordinate expert contributors across technical fields. A strong candidate can break down unfamiliar engineering problems, design data specifications, and carry projects from scoping to delivery with little direction. Leadership, clear communication, and comfort with ambiguity matter as much as technical depth.

How it fits the AI era

The work sits close to how foundation models are trained, since the data and evaluation setups this person helps design feed directly into model improvement. AI tools can speed up drafting, analysis, and coordination, but judging technical quality and deciding what good training data looks like still rests with people who know the engineering domain. The human part is the problem framing and the client relationship.

How it builds AI experience

This role builds hands on experience in how frontier models are evaluated and improved through expert data, which is a specific and growing skill. Candidates can prepare by using AI coding assistants on real engineering tasks and by learning how dataset specifications and reinforcement learning environments are put together. Background in simulation, CAD, or hardware work adds a concrete domain to pair with that.

Worth showing

• Technical problem breakdown
• Expert team coordination
• Python and automation

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About AfterQuery

A San Francisco lab that produces expert-written training data and reinforcement learning environments for AI labs.