Phylo Member of Technical Staff System Engineering

Phylo is an applied research lab building agentic intelligence to accelerate discovery for every biomedical scientist. We believe AI agents will fundamentally transform how biomedical research is done enabling faster and more systematic scientific progress.

Our growing team brings together world class researchers and engineers across AI and biology. Backed by a $13.5M seed round led by a16z Menlo Ventures and Anthropic and advised by Nobel Prize laureate and pioneering biologists Phylo is building the next generation of AI systems for the life sciences.

Were looking for an engineer to build and operate the core systems that power Phylos agentic AI platform in production. Youll design and implement the distributed systems compute environments and service architecture that allow our AI agents to run reliably at scale across cloud-native deployments and enterprise environments.

This is an early foundational role on the team with real ownership over core infrastructure decisions a high degree of autonomy and the ability to meaningfully shape the companys direction from day one.

We are an AI-native engineering team: we use coding agents heavily move fast and hold a very high bar for engineering excellence.

• Design and build production systems that orchestrate agent execution and power AI-driven scientific workloads.

• Build and operate scalable reliable infrastructure across cloud hybrid and on-prem enterprise environments.

• Develop systems for sandboxed execution secure task isolation and controlled compute environments. Design and implement security access control and compliance foundations suitable for enterprise deployments.

• Partner closely with ML and science teams to translate computational workflows into robust production-grade distributed systems.

• 3 years of industry experience in backend infrastructure or distributed systems engineering.

• Strong proficiency in at least one programming language (e.g. Python Go Rust or similar).

• Experience designing and operating distributed systems in production.

• Deep hands-on experience with containerization and Kubernetes.

• Experience with infrastructure-as-code tooling (e.g. Terraform Pulumi or equivalent).

• Experience operating systems on at least one major cloud provider (AWS GCP or Azure).

• Comfort owning systems end-to-end in fast-moving high-autonomy environments.

• Experience building enterprise SaaS platform that supports single-tenant customer hosted deployment patterns.

• Experience in building R&D infrastructure at Pharma/Biotech.

• Experience with job orchestration task scheduling or workflow engines.

• Experience with sandboxed or isolated execution frameworks (e.g. gVisor Kata Containers Firecracker).

• Familiarity with distributed storage observability systems or high-performance compute environments.