Infrastructure Engineer
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Job Description
Infrastructure Engineer building infrastructure and developing CI/CD for clinical AI/ML platform at Bayesian Health. Collaborating with cross-functional teams to ensure reliable and scalable systems.
Responsibilities:
- Build and maintain the infrastructure for the Bayesian platform
- Develop CI/CD to enable other team members such as software engineers, data scientists to accelerate their development
- Propose enhancement to our infrastructure design to manage cloud costs and ensure reliability
- Define a branching and promotion strategy that comply with the regulatory change control process
- Build and maintain CI/CD pipelines using GitHub for automated testing and deployment
- Create infrastructure guidelines and templates such as Terraform modules
- Continuous monitoring of system performance and reliability, and apply software upgrades accordingly
- Collaborate with team members in troubleshooting infrastructure issues and optimizing performance
- Partner with SecOps engineer to implement security best practices complying with HIPAA, HITRUST, FDA, and client requirements
- Architect and build a secure, internal AI Ops platform to host and manage AI/ML agents for infrastructure optimization.
Requirements:
- 5+ years of experience building and operating production cloud infrastructure on AWS as a DevOps, Infrastructure, Site Reliability Engineer, or similar role.
- Proficient with Kubernetes, preferably with EKS, including cluster bootstrapping and day-2 ops.
- Strong operational knowledge of relational databases such as PostgreSQL/MySQL (backups, failover, performance tuning).
- Deep expertise in Terraform (or equivalent IaC) and an eye for building clean and scalable modules.
- Familiarity with observability tools, particularly the Datadog
- Experience building infrastructure with sensitive data that contains PHI/PII.
- Knowledge of CI/CD pipelines, preferably with CircleCI
- Excellent communication skills and a proven ability to collaborate with cross-functional teams (e.g., engineering, data science) to translate requirements into robust technical solutions.
- Experience handling ambiguity and uncertainty in a startup.
Benefits:
- Equal employment opportunities
- Prohibits discrimination and harassment of any type
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