СШАSenior Platform Engineer
1 мес. назад
180k–240k USD / годСШАSeniorOnsite
awsecscideploymentmonitoringautomation
Senior Platform Engineer responsible for improving systems that build, deploy, observe, and operate production services at , focusing on engineering enablement and platform reliability.
О компании
- A small, senior engineering team with high autonomy.
- Application teams own the services they ship. Platform makes that ownership easier with shared infrastructure, tools, and standards.
- Infrastructure changes are reviewed and managed as code.
- High standards for patient safety, privacy, reliability, and code quality.
- is the #1 AI Doctor and the first AI legally authorized to practice medicine. We process millions of consultations monthly, with 99%+ treatment-plan accuracy validated by board-certified clinicians. At .ai , people can receive free, anonymous, HIPAA-compliant AI consultations and connect with human physicians for affordable visits, available 24/7 across all 50 states. raised its seed, Series A, and Series B rounds between February 2025 and January 2026, with backing from Union Square Ventures, Lightspeed Venture Partners, and Abstract.
Обязанности
- gives people free, private access to AI health guidance and affordable visits with human physicians. Millions of consultations already depend on our production systems.
- We are hiring a Senior Platform Engineer to improve the systems used to build, deploy, observe, and operate . This role owns engineering enablement, including the environment in which engineers and coding agents understand the codebase, make changes, validate them, and ship.
- Improve the reliability and operation of production services on AWS ECS.
- Build shared infrastructure, service templates, and delivery workflows that reduce the time from code to production.
- Improve local development, CI, test, and deployment workflows so engineers can work without platform support for routine tasks.
- Build agent-ready repositories, documentation, and interfaces so coding agents can complete useful tasks with less supervision.
- Automate recurring work such as service setup, dependency changes, release checks, and incident triage.
- Create guardrails and feedback loops that make agent-produced changes fast to validate and safe to ship.
- Give engineers useful logs, metrics, alerts, and service health information.
- Define practical standards for incident response, recovery, capacity, and service reliability.
- Build security, privacy, and compliance controls into infrastructure and delivery workflows.
- Track infrastructure cost and improve efficiency as traffic, data, and AI workloads grow.
- Work with product, AI, data, and security engineers to solve production problems.
Требования
- Experience building and operating production systems on AWS.
- Strong knowledge of containers, infrastructure as code, CI/CD, networking, and observability.
- Experience with container orchestration and automated delivery.
- Experience improving developer environments, CI performance, service templates, or internal engineering tools.
- The ability to write software and automation instead of relying on manual procedures.
- Daily experience with coding agents and evidence that you have built tools, context, or workflows that make them more reliable.
- Experience measuring or improving engineering throughput, CI time, test quality, or self-service adoption.
- Experience diagnosing incidents and making follow-up improvements.
- Good judgment about reliability, security, cost, and delivery speed.
- Clear written and verbal communication across engineering teams.
- Many candidates will have 5+ years of relevant experience. Exact tool overlap is not required if your platform fundamentals are strong.
- Experience with AI infrastructure, regulated systems, disaster recovery, or high-traffic applications is useful but not required.
Условия
- Base salary: $180,000 to $240,000, plus equity.
- Benefits reimbursement.
Другое
- Our infrastructure runs on AWS. We use ECS and ECR for container workloads, Terraform and Terragrunt for infrastructure as code, GitHub Actions for CI/CD, and CloudWatch for monitoring. The broader environment includes RDS, DocumentDB, Redis, S3, CloudFront, Application Load Balancers, IAM, and Secrets Manager. Most automation is written in Python or shell.