Infrastructure Engineer

In Brief

• We’re a rapidly growing startup on a mission to make healthcare proactive by empowering physicians, nurses, and care team members with real-time data to save lives.

• You will build and maintain the infrastructure for the Bayesian platform and develop CI/CD to enable other team members such as software engineers, data scientists, etc. to accelerate their development will drive expansion of our clinical AI/ML module offerings, health system enterprise-wide implementations, and revenue growth.

Who We Are

Bayesian Health’s mission is to improve patient outcomes by empowering clinicians with the insights they need to make the right decision for the right patient at the point-of-care. We’re a diverse team of clinicians, engineers, machine learning experts, product designers, and performance improvement leaders committed to enabling smarter, patient-specific care delivery through unlocking the power of data.

We’re funded by top tier tech and biotech investors: Obvious Ventures, Andreessen Horowitz, American Medical Association’s venture arm, Catalio Partners, and LifeForce Capital. Our company has won many awards; most recent recognitions include: Forbes AI Top 50, World Economic Forum Tech Pioneer, Time Best Inventions, BioTech AI Company of the Year.

Read more about our recent publication in Nature Medicine that associates our products with lives saved.

What you’ll do

As an Infrastructure Engineer, you will build and maintain the networking and infrastructure for the Bayesian platform and develop CI/CD pipelines to enable other team members such as software engineers, data scientists, etc. to accelerate their development. This role is crucial to drive expansion of our clinical AI/ML module offerings, health system enterprise-wide implementations, and revenue growth.

Responsibilities

• Design cost-optimized, fault-tolerant infrastructure for scale: Propose enhancement to our infrastructure design to enable us to expand our client base and deploy new products on our platform while managing cloud costs and ensuring reliability.

• Streamline development and deployment: Define a branching and promotion strategy that allow us to comply with the regulatory change control process. Build and maintain CI/CD pipelines using GitHub for automated testing and deployment.

• Establish and evangelize infrastructure best practices: Create infrastructure guidelines and templates such as Terraform modules, and educate team members in leveraging them.

• Infrastructure support and maintenance: Continuous monitoring of system performance and reliability, and apply software upgrades accordingly. Collaborate with other team members in troubleshooting infrastructure issues and optimize performance.

• Secure infrastructure: Partner with SecOps engineer to implement security best practices complying with HIPAA, HITRUST, FDA, and client requirements.

• AI Ops Platform Architecture: Architect and build a secure, internal AI Ops platform to safely host and manage AI/ML agents for infrastructure and DevOps optimization.

Minimum qualifications

• 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.

Preferred qualifications

• Experience with using AI agents to optimize infrastructure management or DevOps workflows.

• Experience with disaster recovery or business continuity plans.

• Experience with multi account, multi cluster topologies.

• Experience building systems in healthcare, life sciences, or similarly regulated industries

• 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.

• Design cost-optimized, fault-tolerant infrastructure for scale: Propose enhancement to our infrastructure design to enable us to expand our client base and deploy new products on our platform while managing cloud costs and ensuring reliability.

• Streamline development and deployment: Define a branching and promotion strategy that allow us to comply with the regulatory change control process. Build and maintain CI/CD pipelines using GitHub for automated testing and deployment.

• Establish and evangelize infrastructure best practices: Create infrastructure guidelines and templates such as Terraform modules, and educate team members in leveraging them.

• Infrastructure support and maintenance: Continuous monitoring of system performance and reliability, and apply software upgrades accordingly. Collaborate with other team members in troubleshooting infrastructure issues and optimize performance.

• Secure infrastructure: Partner with SecOps engineer to implement security best practices complying with HIPAA, HITRUST, FDA, and client requirements.

• AI Ops Platform Architecture: Architect and build a secure, internal AI Ops platform to safely host and manage AI/ML agents for infrastructure and DevOps optimization.

Minimum qualifications

• 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.

Preferred qualifications

• Experience with using AI agents to optimize infrastructure management or DevOps workflows.

• Experience with disaster recovery or business continuity plans.

• Experience with multi account, multi cluster topologies.

• Experience building systems in healthcare, life sciences, or similarly regulated industries

• 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.