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Lead developer - care delivery solutions

Richmond
beBeeSoftware
Developer
Posted: 17 September
Offer description

Transforming Healthcare with Technology

We're on a mission to optimize care delivery, empowering clinicians to focus on patient well-being. Our goal is to create an ecosystem where AI systems complement clinical expertise, reducing administrative burdens and enhancing quality and accessibility of care.

A diverse team of innovators, builders, scientists, and creatives collaborate to drive change. We prioritize agility, achieving milestones in 6 months that others take 4 years to accomplish. Our innovative approach has supported 20 million patient consults in just 12 months, and we continue to power over 1 million consults weekly.

To support our global expansion plans, we need talented individuals like you to join our Engineering team. As a Senior Software Engineer – DevOps, you'll work closely with our Engineering Manager to own the release pipeline, automating build, test, and deploy steps to ensure new models and services reach production quickly and safely.

Your responsibilities will include operating cloud infrastructure (GCP or AWS) using Terraform or similar, balancing performance with cost. You'll develop sensible observability, surface metrics for model-level latency, token usage, and streaming throughput alongside traditional health checks.

You'll manage artefacts, handle model weights, embeddings, and audio assets to maintain version traceability and enable seamless rollbacks. You'll also harden security, apply least-privilege principles, secrets management, and data-handling policies suitable for sensitive health data.

In this role, you'll guide the team, create runbooks, share best practices, and help engineers debug production issues. We seek someone with a strong foundation in Linux, containers, and networking, hands-on experience with IaC (Terraform, Pulumi or similar), and at least one major cloud platform.

Candidates should have CI/CD expertise covering microservices and workloads that include GPUs or other specialized hardware. They should also have working knowledge of monitoring and alerting stacks (Prometheus, Grafana, Cloud native tools) with an eye on AI-specific signals such as model response times and cost per request.

The ideal candidate should be comfortable navigating security and compliance in a data-sensitive environment. Clear communication is key, making complex infra topics accessible to the rest of engineering.

If you are a driven, competitive, and highly motivated operator who excels at problem-solving and building relationships, we want to hear from you.

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