About the job
About Phylo
Phylo is a pioneering applied research laboratory dedicated to the advancement of agentic intelligence aimed at accelerating the discovery process for biomedical scientists. We envision a future where AI agents revolutionize biomedical research, fostering rapid and systematic scientific advancements.
Our expanding team consists of elite researchers and engineers specializing in AI and biology. With a robust $13.5M seed funding round led by top-tier investors such as a16z, Menlo Ventures, and Anthropic, and endorsed by Nobel Prize winners and leading biologists, Phylo is at the forefront of developing next-generation AI systems for the life sciences.
About the Role
We are seeking a skilled engineer to construct and maintain the essential systems that drive Phylo’s agentic AI platform in live environments. You will architect and implement distributed systems, computing frameworks, and service architectures that ensure our AI agents operate reliably at scale, whether in cloud-native settings or enterprise environments.
This position represents a foundational role within our team, granting you substantial ownership over critical infrastructure decisions, a high level of autonomy, and the opportunity to significantly influence the company’s trajectory from day one.
Our engineering team is AI-driven, leveraging coding agents extensively, moving swiftly, and maintaining rigorous standards of engineering excellence.
Responsibilities
Design and develop production systems that orchestrate agent execution and support AI-driven scientific workloads.
Construct and manage scalable, reliable infrastructure across cloud, hybrid, and on-premises enterprise environments.
Oversee enterprise deployment architecture, ensuring secure, reproducible installations for customer-managed infrastructures (VPC, private cloud, on-prem, air-gapped, or regulated environments).
Create systems for sandboxed execution, secure task isolation, and controlled computing environments. Design and implement foundational security, access control, and compliance mechanisms suitable for enterprise deployments.
Collaborate closely with ML and scientific teams to convert computational workflows into robust, production-grade distributed systems.
Requirements
A minimum of 3 years of industry experience in backend, infrastructure, or distributed systems engineering.
Demonstrated proficiency in at least one programming language (e.g., Python, Go, Rust).

