Senior Platform Engineer - Cloud & Developer Experience

Role Description

Bioptimus is building a universal foundation model for biology — learning the deep structure of living systems from data at scale, the way large language models learned the structure of text. Getting this right accelerates drug discovery, protein engineering, and genomics, and ultimately creates lasting impact for patients living with disease.

This is a remote role. We’re headquartered in Paris, but the position can be performed remotely outside of Paris.

As our anchor platform hire on the Cloud & Developer Experience surface, you'll own the AWS foundation, the infrastructure-as-code that defines it, and the self-service paths that let every engineer and researcher provision what they need — safely, repeatably, and without waiting on us.

This is a platform-first, product-minded role. You won't just operate infrastructure; you'll decide what graduates from a one-off script into a paved road, build that paved road as a product other teams genuinely want to use, and set the standards the rest of the team builds on.

What you'll be doing

• Own the cloud foundation.
• Design, build, and own our AWS architecture and the Terraform/IaC that defines it — accounts, networking, identity, core services — as reproducible, reviewed, version-controlled infrastructure.
• Build the self-service platform.
• Create the golden paths and internal developer-platform tooling that let engineers and researchers provision, deploy, and ship with minimal friction and sensible guardrails.
• Own CI/CD and the deployment fabric.
• Build and maintain the pipelines and deployment substrate — including the path that gets our models and SDK into cloud and on-prem/customer environments reliably.
• Engineer security and networking into the platform.
• Make security and a sound network a property of the paved road, not a checklist: IaC for access management and access control, secrets management, least-privilege defaults, network segmentation and private connectivity — so doing the right thing is the easy thing.
• Set the standards.
• Create, influence, and review the architecture, standards, and processes the platform team works to; decide, with a product lens, what becomes platform versus what stays an experiment.
• Make it observable and cost-aware.
• Build the metrics, alerting, and cost visibility that keep the platform reliable and economical as scale grows.
• Support research at scale.
• Bring platform know-how to research workflows and help them self-serve — supporting scale, not owning research-infra execution.

Qualifications

• Proficiency in AWS — hands-on production experience designing and running cloud infrastructure for real workloads.
• Proficiency in Infrastructure-as-Code — Terraform in production (configuration-as-code such as Ansible a plus); you treat infrastructure as reviewed, reproducible software.
• Proficiency in Kubernetes and containers — hands-on with container orchestration and the components around it.
• Strong CI/CD and developer-experience instincts — GitHub Actions, ArgoCD/Flux or equivalent; you've built pipelines and internal tooling that other engineers depend on.
• Security-engineering capability — you implement access control, secrets, and least-privilege in code, and reason about the security posture of what you build.
• Strong networking — hands-on with cloud and hybrid networking (VPC design, segmentation, private connectivity, DNS, load balancing, ingress/egress control).
• A platform-as-a-product mindset — you can tell what deserves to be a productized paved road versus a script, ship opinionated defaults, and enable teams rather than gate them.
• Solid software engineering — Python, Go, or a comparable language, with sound engineering practices.

How to stand out

• Experience with cloud GPU compute for ML training; exposure to HPC (SLURM, InfiniBand, bare-metal GPU) — useful for understanding research workflows even though we run cloud-first.
• Modern observability stacks (Grafana, Prometheus/VictoriaMetrics, Loki).
• Experience in pharma, biotech, healthcare, or another regulated-data environment.
• Exposure to SOC 2, ISO 27001, or GDPR controls.
• Experience contributing to or maintaining open-source projects.
• Start-up or fast-scaling environment, with a high degree of ownership.

Why This is a Unique Opportunity

• Ownership — the autonomy to set direction on the surfaces you own, make the calls, and see the impact.
• Real leverage — you're a force multiplier for every engineer and researcher building on top of the foundation models.
• Foundational work — you're building the platform org from the seed, not maintaining someone else's.
• In addition: a competitive salary and meaningful equity, flexible/remote-friendly working, and significant room for growth at the intersection of AI and biology.

The candidate journey

• Screening: Once you have applied, the hiring team will review your application to determine if your work experience and skills align with the necessary proficiencies of this position.
• Hiring Manager (30 min): A discussion with the Hiring Manager to review your background, operational experience, technical fluency, and motivation for joining Bioptimus.
• Technical Assessment: You will be invited to complete a technical assessment designed to evaluate your practical skills in data operations, data handling, and workflow problem-solving.
• Case Study: You will work through a real-world operational case study related to biomedical data onboarding, harmonization, or partner management.
• Executive Interview: A comprehensive discussion with our Senior Leadership team focused on long-term vision, collaboration style, values, and mutual fit.
• Offer: Following the completion of the interviews, our hiring team will make a final decision and will be in touch to share the outcome of your interviews.
• Onboarding: We are happy to have you joining the team. Once you have accepted and signed your offer, we will be in touch to begin the process of onboarding you to Bioptimus.