Software Engineer

About The Role

At Autopoiesis Sciences, we're building the foundation for scientific superintelligence: AI that can autonomously advance knowledge across every scientific discipline. We're first developing an AI co-scientist that applies the same systematic doubt and verification that drives human scientific breakthroughs, establishing the reasoning capabilities necessary for true scientific autonomy. This represents the critical first stage toward systems that can eventually operate laboratories autonomously, design their own research programs, and pursue discoveries beyond human imagination. Backed by leading venture capital firms and with thousands of scientists from top universities already requesting early access, we're currently preparing to release our AI co-scientist to the scientific community.

Location

Autopoiesis Sciences is headquartered in San Francisco, and we're expanding our engineering team to Toronto to tap into Canada's exceptional AI and engineering talent ecosystem. This is a fully remote position for candidates based in the Greater Toronto Area.

Technical Focus Areas

• Distributed systems architecture for large-scale AI training and inference
• Production infrastructure for autonomous agent systems
• High-performance computing and optimization
• Data pipeline engineering for scientific datasets
• System reliability, monitoring, and observability
• API design and service architecture
• Database systems and knowledge graph infrastructure
• Deployment systems and MLOps tooling

Autopoiesis Sciences is seeking exceptional Software Engineers to build the robust, scalable infrastructure that powers scientific superintelligence. As a Software Engineer, you will architect and implement the production systems that enable our AI co-scientist to operate at scale across thousands of researchers and scientific disciplines. You'll work at the intersection of cutting-edge AI research and world-class engineering, translating breakthrough algorithms into reliable, performant systems. This role offers the opportunity to solve unique technical challenges that don't exist anywhere else: building infrastructure for AI systems that conduct scientific research autonomously. We're looking for engineers who are obsessed with elegant system design, performance optimization, and building tools that researchers love to use.

Responsibilities

• Design and build highly scalable distributed systems that support massive-scale training, inference, and deployment of autonomous scientific agents
• Architect production infrastructure for AI systems that perform complex multi-step reasoning, literature analysis, and hypothesis generation across scientific domains
• Build robust data pipelines and storage systems that handle diverse scientific datasets, research papers, experimental results, and knowledge graphs
• Develop comprehensive monitoring, observability, and debugging tools for complex AI agent behavior in production environments
• Optimize system performance across the stack, from low-level computational efficiency to high-level service architecture
• Create developer tools and APIs that enable research scientists to rapidly iterate on new capabilities while maintaining production reliability
• Collaborate with ML researchers to translate novel algorithms into production-ready implementations that scale
• Drive technical decisions around infrastructure, tooling, and architecture that will shape how scientific AI systems operate for years to come

Qualifications

• Strong systems programming and software engineering fundamentals with experience building production infrastructure at scale
• Proven ability to design distributed systems, databases, and high-throughput data processing pipelines
• Experience with ML infrastructure, training systems, or deployment of large-scale AI models
• Solid understanding of ML concepts and familiarity with modern AI systems (LLMs, agents, multi-step reasoning)
• Track record of writing clean, maintainable code and making pragmatic engineering tradeoffs
• 3+ years of software engineering experience in production environments
• Bachelor's degree minimum in Computer Science, Engineering, Mathematics, Physics, or related technical field (advanced degree preferred but not required)

Get To Know Us

We're a dedicated team of scientists, researchers, and engineers who believe deeply in the transformative potential of our work. You'll work closely with our leadership team including Chief Executive Officer Joseph Reth (Attended University for CS at 14, former DARPA), Chief Business Officer Dr. Eike Gerhardt (University of Tübingen PhD, University of Tübingen staff), and Chief Scientist Dr. Larry Callahan (University of Chicago PhD, former FDA, former NIH).

Application Process: Due to the high volume of automated applications, we only accept applications through LinkedIn as it helps us connect with genuine candidates. We have systems in place to detect automated submissions and strongly advise against using bots or automated tools in your application process. Please be human in your approach.

Equal Opportunity: Autopoiesis Sciences, Inc. is an equal opportunity employer committed to diversity and inclusion. We welcome applications from all qualified candidates regardless of race, gender, age, religion, sexual orientation, or any other legally protected characteristics.