Infrastructure Engineer

Bayesian Health; United States; On-site; USD 100,000 - 140,000; Full time

Job summary

Bayesian Health, located in the United States, is looking for an Infrastructure Engineer to build and maintain networking and infrastructure for the platform. This role involves designing scalable infrastructure, developing CI/CD pipelines, and ensuring security compliance. The ideal candidate should have over 5 years of experience with AWS, excellent skills in Terraform and Kubernetes, and knowledge in handling PHI/PII data. Join a startup that aims to improve patient outcomes through real-time analytics.

Qualifications

• 5+ years building production cloud infrastructure on AWS.
• Proficiency with Kubernetes, preferably EKS.
• Operational knowledge of relational databases like PostgreSQL or MySQL.
• Strong skills in Terraform and clean module design.
• Experience with observability tools, especially Datadog.
• Experience building infrastructure for PHI/PII data.
• Knowledge of CI/CD pipelines, preferably CircleCI.
• Excellent communication and collaboration skills.
• Comfort handling ambiguity in a startup environment.

Responsibilities

• Design cost-optimized and fault-tolerant infrastructure.
• Streamline development and deployment with CI/CD pipelines.
• Establish infrastructure best practices and guide the team.
• Support ongoing monitoring, upgrades, and optimization.
• Secure infrastructure in partnership with SecOps.
• Architect a secure AI Ops platform.

Skills

Production cloud infrastructure on AWS

Kubernetes

Relational databases (PostgreSQL, MySQL)

Terraform (IaC)

Observability tools (Datadog)

CI/CD pipelines

Excellent communication skills

Collaboration across teams

Job description

Who We Are

Bayesian Health is a startup focused on improving patient outcomes by providing real‑time clinical data analytics to clinicians.

What You’ll Do

As an Infrastructure Engineer, you will build and maintain networking and infrastructure for the Bayesian platform and develop CI/CD pipelines to enable the team.

Responsibilities

• Design cost‑optimized, fault‑tolerant infrastructure that is scalable and cost effective.
• Streamline development and deployment with a branching strategy, CI/CD pipelines, and automation.
• Establish and evangelize infrastructure best practices, guide team on Terraform modules.
• Support ongoing monitoring, upgrades, troubleshooting, and performance optimization.
• Secure infrastructure in partnership with SecOps following HIPAA, HITRUST, FDA requirements.
• Architect a secure AI Ops platform to host and manage AI/ML agents.

Minimum Qualifications

• 5+ years building production cloud infrastructure on AWS (DevOps, SRE, or similar).
• Proficiency with Kubernetes, preferably EKS, cluster bootstrapping and day‑2 ops.
• Operational knowledge of relational databases such as PostgreSQL or MySQL.
• Strong Terraform (IaC) skills and clean module design.
• Experience with observability tools, especially Datadog.
• Experience building infrastructure for PHI/PII data.
• Knowledge of CI/CD pipelines, preferably CircleCI.
• Excellent communication skills and ability to collaborate across teams.
• Comfort handling ambiguity in a startup environment.

Preferred Qualifications

• Experience using AI agents to optimize infrastructure or DevOps workflows.
• Experience with disaster recovery or business continuity plans.
• Experience with multi‑account, multi‑cluster topologies.
• Experience building systems in regulated industries such as healthcare or life sciences.
• Chaos engineering or game‑day facilitation.
• Experience implementing and maintaining a GitOps framework.

Bayesian Health provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.