At FirstPrinciples, we're building Theo, the AI platform for R&D teams. By bringing together an organization's data, the world's research, and their choice of AI models and tools, we're creating a unified platform designed for verifiable scientific work.
We're a small, ambitious team at an early stage of growth, tackling complex technical challenges and building something with the potential to meaningfully change how R&D teams work.
We're looking for people who thrive in fast-paced environments, take ownership, adapt quickly, and aren't afraid to experiment. You'll have the opportunity to make a meaningful impact, work closely with talented people across disciplines, and help shape both our technology and the company as we grow.
The Role:We are seeking a Senior Engineering Manager to lead a team of four to six engineers building core capabilities for Theo and our scientific research platform.
You will develop exceptional engineers, set technical direction, and turn ambitious research ideas into reliable systems. You will operate in a matrixed organization, bringing together specialists from engineering, AI research, physics, simulation, infrastructure, and product into multidisciplinary squads.
A central part of the role is creating a tight feedback loop between research and engineering. You will help researchers and engineers shape solutions together, evolve promising prototypes collaboratively, and preserve scientific insight as experimental systems become robust, scalable products.
This is a hands-on leadership role for someone comfortable moving between people development, architecture, execution, and frontier research.
What You’ll DoManage, coach, and develop a team of four to six engineers.
Form and lead multidisciplinary squads around clear scientific and product outcomes.
Translate open-ended research goals into technical strategies, milestones, and well-designed systems.
Partner closely with researchers and physicists from early exploration through implementation and production.
Create effective paths for researchers to contribute prototypes, algorithms, evaluations, and domain-specific code alongside engineers.
Help experimental systems mature without losing the ideas and assumptions that made them scientifically valuable.
Guide architecture, interfaces, technical standards, and major implementation decisions.
Establish clear ownership and decision-making across teams and reporting lines.
Balance research velocity with reliability, maintainability, reproducibility, security, and cost.
Build strong practices for testing, evaluation, observability, documentation, deployment, and operational ownership.
Stay close enough to the work to review designs, diagnose difficult problems, and contribute directly when it has high leverage.
Influence engineering strategy, hiring, organizational design, and technical culture beyond your immediate team.
Significant software engineering experience building complex systems.
Experience managing and developing high-performing engineers, with a demonstrated ability to raise the velocity and accountability of engineering teams in a sustainable fashion.
A bias for action and iterative delivery, while maintaining high technical standards.
Strong technical judgement across architecture, implementation, and production operations.
Strong execution judgement of knowing when to explore, when to decide, when to simplify, and when to push a team toward completion.
Experience leading cross-functional or matrixed teams without relying on direct authority.
A record of turning ambiguous ideas or prototypes into dependable capabilities.
The ability to build trust and shared language across engineering and research disciplines.
Scientific curiosity and the technical humility to learn from deep domain experts.
Strong communication, facilitation, and conflict-resolution skills.
A pragmatic, low-ego leadership style grounded in evidence and clear reasoning.
Comfort operating where the problem, solution, and path to delivery may all be uncertain.
AI, machine learning, agentic systems, simulation, scientific computing, or research infrastructure.
Model engineering, applications, cloud infrastructure, distributed systems, or developer platforms.
Moving research prototypes into scalable, maintainable products.
Designing systems where evaluation, provenance, reproducibility, or scientific validity matter.
Working with physicists, mathematicians, or other research-intensive teams.
Leading remote and globally distributed teams.
You will help define how engineers, AI researchers, and physicists work together to build a new kind of scientific instrument—one capable of contributing to humanity’s understanding of the universe.
Please submit a resume and cover letter describing your leadership experience, technical background, and interest in our mission. Include “Senior Engineering Manager” in your cover letter.
.png)
