Senior Platform Engineer — Cloud & Developer Experience

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.

Training and serving models of this kind is a serious infrastructure problem: data-rich, compute-hungry, and held to the trust and compliance bar our pharma and research partners expect. The platform that makes this fast, economical, and safe is what this role is here to build.

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

About the role

We are standing up the platform organization that will carry Bioptimus into its next phase of scale. 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. You hold strong opinions and ship opinionated defaults — but you enable, you don't block.

You'll work cloud-first (AWS) and partner closely with research to support their scale, without taking over the research-infra work other teams own.

What you'll be doing

As a Senior Platform Engineer, you will own the following tasks:

• 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.

What you'll bring

The successful candidate will have a ‘team-first’ attitude; be highly organized, proactive, and detail-oriented; thrive in a fast-paced and evolving environment; and enjoy solving operational and technical challenges at scale. We value individuals who combine strong project management capabilities with hands-on technical fluency and an understanding of biomedical data ecosystems.

• 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). You treat the network as a first-class security and reliability surface — this complements the security-engineering work directly.
• 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 (we build the engineering so certification is easy later).
• 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

We believe the best platforms come from ownership, strong opinions, and a genuine instinct to make other people faster. Here's what you can expect:

• 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.