Principal Platform Engineer, AI Engineering

🔥 16 hours ago

🇺🇸 United States – Remote

💵 $190k - $235k / year

⏰ Full Time

🔴 Lead

🏗️ Platform Engineer

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RxSense

WebsiteLinkedInAll Job Openings

201 - 500 employees

💼 Consulting

📦 Logistics

🏥 Healthcare

💰 Private Equity Round on 2020-05

Consulting • Logistics • Healthcare

RxSense is a HealthTech company dedicated to modernizing pharmacy benefit management. They develop cutting-edge products that optimize claims adjudication and analysis, aiming to lower costs and improve access within the pharmacy ecosystem. RxSense offers solutions for PBMs, pharmacies, pharma manufacturers, payers, and consumers, supporting better outcomes for millions of people daily. Their products include advanced tools like the RxIQ Enterprise adjudication engine, business intelligence analytics platform, and AI-based pricing optimization. They are known for their flagship prescription savings brand, SingleCare, which helps consumers secure affordable prices while benefiting pharmacy partners.

📋 Description

• Design and maintain a Terraform monorepo across development, QA, staging, and production • Operate EKS clusters end to end, including node lifecycle, autoscaling, ingress, workload identity, secrets delivery, and cluster security • Build push-based CI/CD on self-hosted GitHub Actions runners with immutable artifacts and enforced promotion flows • Maintain shared Helm chart libraries and per-service charts for backends, frontends, and scheduled jobs • Create golden paths so new services launch with logging, metrics, secrets, identity, and pipelines wired in • Establish least-privilege IAM, secrets management, network boundaries, image provenance, and production guardrails • Establish cloud cost tagging and allocation, right-size compute, and keep spend predictable as traffic, data, and model inference grow • Build default structured logging, metrics, tracing, and cross-service correlation using versioned telemetry contracts • Define platform conventions for tagging, naming, DNS, versioning, and security; document decisions and review infrastructure and deployment changes • Mentor engineers and partner with application, data, and AI engineering teams on platform contracts and promotion environments

🎯 Requirements

• 8+ years building and operating production platform infrastructure (not a hard cutoff; strong candidates with less experience may be considered) • Hands-on production Kubernetes experience, including cluster lifecycle, autoscaling, ingress, workload identity, secrets delivery, and hardening; EKS preferred • Terraform infrastructure-as-code experience at scale, including module design, state layout across environments, and provider upgrades • Experience building or substantially rebuilding CI/CD systems, with artifact immutability and build-once/promote-everywhere delivery • Experience running self-hosted GitHub Actions runners at scale • Hands-on AWS experience with IAM, VPC networking and DNS, secrets management, container registries, and managed compute • Hands-on Helm experience at scale, including shared chart libraries, templating boundaries, and environment configuration • Experience with GitOps or push-based deployment workflows • Experience building service templates, golden paths, self-service tooling, and documentation • Observability implementation experience with structured logging, metrics, and distributed tracing; examples include OpenTelemetry, Prometheus/Grafana, and Datadog • Practical security experience in regulated or security-sensitive environments, including least-privilege IAM, secrets hygiene, network isolation, image provenance and scanning, and PHI/PII handling • Experience supporting data workloads on Kubernetes, such as Spark, Kafka, Airflow, or Dagster • Cloud cost ownership experience, including tagging, allocation, right-sizing, and measurable spend reduction without degrading reliability • Production coding experience and working fluency in at least one backend language such as Python, Go, or C#/.NET; shell proficiency • Excellent communication and collaboration skills • Experience mentoring engineers and setting extensible infrastructure standards • Comfort working in a small, fast-moving team and wearing multiple hats