Sobre esta vaga de Staff Platform Engineer na Redoxengine
Opportunity & Impact
Redox is on a mission to accelerate healthcare’s transformation with useful data. The Redox Engine, a flexible interoperability platform, connects and powers real-time healthcare data exchange. With just one connection, data can be orchestrated across a growing network of 12,000+ systems and organizations, including 100+ electronic health record systems (EHRs). Redox processes over 1.2 billion messages per month across our health tech vendor, provider, payer, EHR, and life sciences customers.
We’re a fully remote team within the U.S. that operates with radical transparency and a strong bias toward ownership.
Impact on Team
The Platform Team at Redox Engineering builds the foundations that let application developers ship reliably: the automation, guardrails, and infrastructure that power how healthcare data moves securely through our systems.
The platform is entering a new chapter. We’re building toward a platform where AI agents take part in engineering, operations, and everyday work, alongside the people who build on it. Getting there means keeping security, stability, and scale as the baseline while traffic grows and agents gain autonomy, making costs knowable to the people who make decisions, and steadily simplifying the platform so the right thing is the easy thing.
We’re looking for a Staff Platform Engineer who is a highly capable, hands-on contributor. You’ll pick up an ambiguous lane of work, scope it, prototype and experiment, and then carry it all the way to production-ready code. You’ll bring deep cloud and Kubernetes experience and sound judgment, and you’ll work with the team to shape and align on where the platform goes next.
Software Platform/Tools: AWS, Docker, EKS; GitHub Actions (CI), ArgoCD (CD), Atlantis; Kyverno, Karpenter, KEDA, VPA, Velero, Crossplane; Prometheus, Grafana, InfluxDB, Sumo Logic, Mimir, OpenTelemetry; Terraform, Helm; Postgres, Redis; Kafka; Node.js/TypeScript and Python services.
What you'll be doing:
Own an ambiguous lane of platform work end to end: scope it, prototype and experiment, then turn what works into production-ready code
Build the foundations that let AI agents safely take part in engineering and operations: where they run, how they’re permissioned, and how their actions are observed and audited
Keep security, stability, and scale as the baseline as traffic grows and agents gain autonomy, partnering with InfoSec to harden the platform and reduce single points of failure
Simplify the platform over time: consolidate tools, vendors, and patterns so humans and agents can do the right thing because it’s the easy thing
Automate recurring upkeep wherever practical, so necessary maintenance takes less human effort
Help make platform and AI costs understandable to the people making commercial, operational, and technical decisions
Co-create the platform’s direction with the team and our platform architect: bring informed opinions, calibrate with others, and align your work to where we’re headed
Contribute hands-on across the platform, including infrastructure, CI/CD, container orchestration, and observability. This is an IC role.
Participate in on-call and own the systems you build, including production incidents
Share knowledge with a highly senior team of peers through pairing, design reviews, and documentation
What you'll bring:
8+ years in cloud-native infrastructure or platform engineering roles, with demonstrable progression in technical scope and impact
Deep, hands-on AWS experience running production systems, including networking, IAM, and managed services
Production Kubernetes expertise, including cluster lifecycle, upgrades, node management, and autoscaling. You’ve operated it, not just deployed it.
Strong infrastructure-as-code practice (Terraform/HCL, Helm) and experience with GitOps-style delivery
A track record of automating operational work, with the testing and rollback safety that makes speed possible
A security-minded approach to access, secrets, and configuration, ideally in a regulated environment
High output on ambiguous problems: you’ve taken loosely defined work from prototype to production, and you know when an experiment is ready to harden
Sound judgment and strong written communication: you write clear proposals with tradeoffs, calibrate with peers, and commit once a direction is set
Nice to have in your background:
Experience in a fully remote, growth-stage, or regulated-industry company (HIPAA, HITRUST, SOC 2)
Building or operating AI agents in production, or applying AI to infrastructure and operations work
Observability depth: OpenTelemetry, distributed tracing, or managed observability platforms
Networking depth: site-to-site VPNs, IPsec, or high-throughput messaging systems
Developer enablement work: you’ve thought about the internal developer experience, not just the ops side
Cost visibility or FinOps experience in cloud environments
