Software Engineer, Infrastructure

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 Areas of Focus

• Scalable distributed computing systems for AI workloads
• High-performance data pipelines and real-time processing
• Fault-tolerant microservices architecture and orchestration
• Advanced monitoring, observability, and system reliability
• Secure API design and integration frameworks
• Database optimization and distributed data management
• Container orchestration and infrastructure as code
• Performance optimization and resource management

Autopoiesis Sciences is seeking an exceptional Software Engineer to architect and build the robust, scalable infrastructure that powers scientific superintelligence. As a Software Engineer, you will design and implement the foundational systems that enable our AI co-scientist to operate at massive scale with absolute reliability. Our infrastructure demands the highest standards of engineering excellence: clean, maintainable code, elegant system design, and obsessive attention to performance and reliability. This role offers the opportunity to build infrastructure that could fundamentally transform how scientific discovery is conducted across all disciplines. We're looking for engineers who take deep pride in crafting beautiful, efficient systems and have an uncompromising commitment to engineering excellence.

Responsibilities

• Design and implement massive-scale distributed backend systems that support autonomous AI agents performing complex scientific reasoning, literature analysis, and experimental design
• Architect fault-tolerant microservices and APIs that handle high-throughput scientific data processing with sub-millisecond latency requirements
• Build robust data pipelines that can ingest, process, and serve petabytes of scientific literature, experimental data, and research outputs with perfect reliability
• Design and optimize database systems and caching layers that support complex scientific queries across multiple domains while maintaining ACID compliance
• Implement comprehensive monitoring, logging, and observability systems that provide deep insights into system performance and enable proactive issue resolution
• Develop infrastructure-as-code solutions that enable rapid, reliable deployments across multiple environments while maintaining strict security and compliance standards
• Lead performance optimization initiatives, identifying and eliminating bottlenecks to ensure systems operate at peak efficiency under extreme load
• Collaborate with research staff to design specialized infrastructure that supports distributed training, inference, and model serving at unprecedented scale
• Champion engineering best practices including code reviews, automated testing, documentation, and system design principles that ensure long-term maintainability

Qualifications

• Strong experience designing and implementing large-scale distributed systems with proven track record of handling high-traffic production workloads
• Expert-level proficiency in Python with deep understanding of performance characteristics and optimization techniques
• Extensive experience with cloud platforms (Oracle Cloud Infrastructure, AWS, GCP, Azure) and container orchestration systems (Kubernetes, Docker)
• Deep knowledge of database systems (PostgreSQL, MongoDB, Redis) and distributed data technologies (Kafka, Elasticsearch)
• Experience with infrastructure-as-code tools (Terraform, Ansible) and CI/CD pipeline design
• Strong understanding of system design principles, microservices architecture, and API design patterns
• Experience with monitoring and observability tools (Prometheus, Grafana, ELK stack)
• 3+ years of backend engineering experience with demonstrated expertise in building scalable, maintainable systems
• Bachelor's degree minimum in Computer Science, Software Engineering, or related technical field; Master's preferred
• Passionate commitment to clean code, elegant system design, and engineering excellence

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), Chief Scientist Dr. Larry Callahan (University of Chicago PhD, former FDA, former NIH), and our newly announced President and Head of Scientific Superintelligence Kavita Kulkarni (former Global Head of Strategy and Partnerships for Biomedical Superintelligence at Google, core team member for Google's AI Co-Scientist).

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.