Staff Platform Engineer

$175k–$225k base
• Full-time

Radimal is a veterinary radiology and AI diagnostics platform delivering 24/7 imaging insights to hospitals nationwide. We combine board-certified radiologists with advanced AI to support real-time clinical decision-making for patients when it matters most.

Our platform spans high-throughput medical imaging, GPU-backed inference, global distribution, and enterprise-grade reliability. As we scale, we're investing in senior platform ownership to make the system safer, more predictable, and easier for engineers to build on.

Why This Role Exists

Radimal has grown quickly. While the platform is working, operational ownership has been too diffuse. Reliability, on-call clarity, and platform standards need a single senior owner who can reduce noise, establish guardrails, and make the system more predictable as we scale.

This role exists to bring focus, ownership, and calm to the platform layer.

The Role

We're hiring a Staff Platform Engineer to own the technical foundations that enable Radimal's engineering teams to move quickly and reliably.

This is a senior, hands-on role with real accountability for platform architecture, infrastructure, and production systems. You'll own DevOps, reliability, and on-call systems, with authority to investigate and diagnose issues across the full stack.

You will not be expected to do everything at once. Success comes from establishing ownership, setting priorities, and making the system more predictable over time.

A core part of this role is operational containment and reliability ownership. You'll reduce operational burden on product and AI teams by owning platform standards, tooling, and reliability so others can focus on building.

You'll work closely with the CEO and VP of Engineering on platform strategy, architectural tradeoffs, and operational risk, while maintaining clear ownership of production systems.

This role is for someone who wants true ownership and influence through execution, not advisory distance.

What You Will Own

Platform Engineering

Own the core platform foundations that support all product and AI development

Build shared infrastructure, libraries, and patterns that make it easier to ship safely

Establish clear interfaces and ownership boundaries so teams can move independently

Improve developer experience through better CI/CD, local tooling, and observability

Raise the overall operational maturity of the engineering organization

Infrastructure and Cloud

Own and evolve Radimal's AWS and Terraform footprint

Lead deployments across ECS, Fargate, EC2, containerized services, and GPU workloads

Manage and improve workloads running on Render and Modal

Make architectural decisions for scale, reliability, and cost efficiency

Engineering Enablement

Reduce operational burden on product and AI engineers by owning reliability and tooling

Create guardrails that increase safety without slowing development

Enable engineers to self-serve infrastructure and diagnostics where appropriate

Reliability, On-Call, and Operations

Own production uptime, SLOs, and operational health

Design and own on-call coverage and escalation models

Serve as senior escalation during incidents while building systems that minimize the need for escalation

Lead incident response and post-incident reviews with clear accountability

Eliminate ambiguity around who owns production at all times

Over time, success in this role means fewer incidents, fewer escalations, and a platform that largely runs without heroics.

Observability and Performance

Operate and extend Grafana and Prometheus monitoring stacks

Improve alerting, diagnostics, and operational visibility

Build high-availability and fault-tolerant architectures

Implement caching, CDN, and performance strategies for global scale

Full-Stack Investigation

Investigate production issues across infrastructure, backend services, data pipelines, AI inference workflows, and frontend behavior

Trace request flow end to end across GraphQL APIs, Python services, and React applications

Read and debug React code as needed to understand client-side behavior and API usage

Form and test hypotheses during incidents to drive fast, accurate resolution

Know when to dive deep personally and when to pull in specialists

ML Ops and AI Platform Support

Understand ML Ops fundamentals including model deployment, versioning, and monitoring

Support GPU-backed inference workloads and AI service reliability

Partner with AI engineers to ensure models are observable, debuggable, and production-ready

Identify and mitigate operational risks related to model performance, latency, and failures

Leadership and Collaboration

Partner with the CEO and VP of Engineering on platform strategy and architectural tradeoffs

Provide clear, grounded assessments of platform risk and readiness

Act as a trusted technical owner during high-impact decisions and incidents

Align platform reliability with product and business goals

Security and Compliance

Strengthen infrastructure security and access controls

Support enterprise security reviews, penetration testing, and SOC 2 readiness

Improve auditability, monitoring, and operational hygiene

What We're Looking For

7+ years operating production systems at scale

Strong Python experience for automation and backend tooling

Deep AWS experience (ECS, Fargate, EC2, ECR, RDS, CloudFront, IAM)

Strong Terraform, Docker, CI/CD, and infrastructure-as-code expertise

Hands-on experience with Grafana and Prometheus

Experience with Postgres and modern backend architectures

Strong understanding of distributed systems, caching, and performance

Comfort debugging across GraphQL APIs, Python services, and React frontends

Working knowledge of ML Ops concepts and AI inference systems

Clear communicator with a strong ownership mindset

Bonus Experience

Medical imaging or DICOM workflows

GPU compute, AI inference, or ML pipeline integration

Enterprise security reviews or penetration testing

GraphQL or Hasura-based platforms

Why Join Radimal

High ownership of a mission-critical clinical platform

Deep technical challenges with real patient impact

Clear mandate and authority to shape how engineering works

Fully remote team with high trust and low bureaucracy

Opportunity to grow into broader technical leadership over time