Member of Technical Staff - Infrastructure

Job summary

Design, build, and operate the infrastructure and deployment foundations for an enterprise AI platform. This includes managing Kubernetes-based systems, cloud-native environments, and supporting scientific computational workloads for biotech and pharma customers.

Job details

About Phylo 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. About the role We’re looking for an Infrastructure Engineer to build, operate, and scale the deployment foundations for Phylo’s enterprise AI platform. This role is focused on the systems that let Phylo run reliably in real-world customer environments: cloud infrastructure, Kubernetes, secure single-tenant deployments, observability, networking, storage, and operational workflows. You’ll help bring Phylo’s agentic AI platform into enterprise pharma, biotech, and research environments where security, reliability, data isolation, and deployment discipline matter deeply. You’ll work closely with engineering, ML, science, and customer-facing teams to make Phylo easy to deploy, monitor, support, and scale across cloud and customer-managed environments. What You’ll Work On Design, build, and operate infrastructure for Phylo’s enterprise deployments, including single-tenant and customer-hosted environments. Build deployment systems for cloud-native and enterprise environments, own Kubernetes-based infrastructure for Phylo services, sandboxed agent execution, compute workloads, storage mounts, networking, and observability. Support infrastructure for scientific and computational workloads, including HPC-adjacent workflows, bioinformatics tools, batch execution, GPU/CPU compute, and large-scale file/data movement. Work with customer-facing teams to support enterprise deployment planning, debugging, reliability reviews, and production operations. Help define the long-term architecture for deploying Phylo into pharma, biotech, academic, and research environments. Requirements 2+ years of industry experience in infrastructure engineering, DevOps, SRE, platform engineering, cloud engineering, or a similar role. Strong hands-on experience with Kubernetes in production. Experience deploying and operating systems on AWS, GCP or Azure. Experience with infrastructure-as-code tools such as Terraform, Pulumi, CDK, or similar. Strong understanding of networking, IAM, VPCs, load balancers, DNS, certificates, secrets management, and cloud security fundamentals. Experience building CI/CD pipelines, deployment automation, environment provisioning, and operational tooling. Nice to Haves Experience deploying enterprise SaaS into single-tenant, customer-hosted, VPC-isolated, or regulated environments. Experience building or maintaining R&D infrastructure in pharma, biotech, academic research, or life sciences organizations. Experience with HPC, bioinformatics infrastructure, scientific computing, workflow engines, or batch schedulers. Experience with tools or systems such as Nextflow, Snakemake, Cromwell, Slurm, AWS Batch, EKS, ECS, FSx, Lustre, S3, or distributed filesystems. Experience with secure sandboxing or isolated execution environments such as gVisor, Kata Containers, Firecracker, or Kubernetes sandboxing. Experience supporting GPU-enabled workloads, large-scale data processing, or scientific compute clusters. Experience with enterprise identity, SSO, audit logging, compliance controls, customer networking, VPNs, private connectivity, or data residency requirements. Experience working directly with enterprise customers during deployment, onboarding, debugging, or production support. Why Join Us? Competitive salary and equity share in building the future of biomedical discovery Full medical, dental, and vision coverage, including free therapy sessions and eyewear stipend 401(k) to help you build long-term financial security (US only) Unlimited PTO to recharge when you need it (US only) Lunch and snacks when you're in the office Regular team offsites and company events A culture of excellence and speed - we move fast, think big, and support each other every step of the way Your work will directly impact our mission to 100X biomedical discoveries through AI

What you’ll do

Design, build, and operate the infrastructure and deployment foundations for an enterprise AI platform. This includes managing Kubernetes-based systems, cloud-native environments, and supporting scientific computational workloads for biotech and pharma customers.

Requirements

Requires 2+ years of industry experience in infrastructure, DevOps, or SRE roles with strong production experience in Kubernetes and major cloud providers. Proficiency in infrastructure-as-code tools and a deep understanding of cloud networking and security are essential.

Benefits

• Competitive Salary
• Equity Share
• Medical Insurance
• Dental Insurance
• Vision Insurance
• Free Therapy Sessions
• Eyewear Stipend
• 401(k)
• Unlimited PTO
• Lunch and Snacks
• Team Offsites

Listed skills

• Kubernetes · Preferred
• Production · Preferred
• Technical · Preferred
• CI/CD · Preferred
• Reliability · Preferred
• staff · Preferred
• Teams · Preferred
• Execution · Preferred
• Amazon Web Services · Preferred
• Audit · Preferred
• batch · Preferred
• Customer · Preferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

• Kubernetes
• AWS
• GCP
• Azure
• Terraform
• Pulumi
• CDK
• Infrastructure as Code
• CI/CD
• Networking
• IAM
• VPC
• Cloud Security
• SRE
• DevOps
• Platform Engineering

Job areas

• Technology
• Software
• Engineering
• Science & Research
• Healthcare

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