Senior Platform Engineer

About Us

Health Data Analytics Institute (HDAI) is a commercial-stage HealthTech company. Our Intelligent Health Management System, HealthVision™, is a first-in-class enterprise solution leveraging real-time predictive analytics and generative AI to deliver improved outcomes, efficiencies, and economics for health systems and value-based care organizations.

HDAI is located in Dedham, MA near the Dedham Corporate Center Commuter Rail station on the Franklin/Foxboro line (25 minutes from Back Bay and South Station, Boston) and I-95/128.

Summary

We are looking for a Senior Platform Engineer to join the Platform Engineering team at HDAI. You will be a core contributor to the infrastructure that powers HealthVision, a clinical analytics platform that processes data for health systems through serverless pipelines running AI inference, LLM-powered summaries, and real-time patient analytics on AWS.

The platform runs across hundreds of AWS accounts in a multi-tenant model with per-customer isolation, orchestrated through Terraform and GitHub Actions. You will work across the full infrastructure stack: ECS, Lambda, DynamoDB, MongoDB, S3, SQS, VPC networking, and CI/CD. There are legacy systems to retire, cost to cut, and automation to build.

You will have real ownership, work closely with the Manager of Platform Engineering, and collaborate across engineering. We expect you to use AI tools daily to multiply your output.

Responsibilities

Infrastructure delivery. Build and maintain AWS infrastructure through Terraform. Write shared modules, manage per-customer workspaces, and ensure environments are reproducible and version-controlled. You'll be executing infrastructure changes across hundreds of workspaces regularly.

Automation and tooling. Build internal tools and automation that reduce manual work across the engineering organization: CI/CD pipeline improvements (GitHub Actions, including our self-hosted runner fleet), deployment tooling, customer onboarding automation, environment provisioning, operational scripts.

Migration execution. Help move workloads onto the compute and data stores that fit them best, retiring legacy systems along the way. Plan and execute migrations, move data safely, and decommission old infrastructure.

Reliability and observability. Improve monitoring and alerting across the platform using Datadog and CloudWatch. Participate in incident response and post-incident reviews.

Security and compliance. Implement HIPAA-compliant infrastructure patterns: IAM least-privilege policies, encryption at rest and in transit, network isolation, audit logging, and data retention controls. Partner with the Security and Compliance team to maintain our SOC 2 and HITRUST posture.

Cost optimization. Identify and implement cost savings: S3 lifecycle policies, right-sizing compute, eliminating unused resources, consolidating per-account overhead. Build cost visibility tooling and alerts.

Cross-team collaboration. Everyone who ships on this infrastructure is your customer, and Product Engineering is your closest one. Learn their workloads well enough to tell them a better way to run them.

Quali fi cations

Required:

5+ years of experience in cloud infrastructure, DevOps, platform engineering, or SRE.

Strong hands-on AWS experience across core services: Lambda, DynamoDB, S3, SQS, IAM, VPC, CloudWatch, ECS/Fargate.

Terraform proficiency: modules, workspaces, state management, CI/CD-driven plan/apply.

Experience with CI/CD pipelines and deployment automation (GitHub Actions preferred).

Comfort with Python (our pipeline services are Python-based) and/or TypeScript.

AI-native engineering practice. You use AI tools (Claude Code, Copilot, or similar) as a core part of your daily workflow.

Linux and networking fundamentals, and the security instincts to handle patient data carefully.

Clear written and verbal communication. You collaborate closely and communicate proactively with team members on a daily basis.

A self-starter who can independently own problems from identification through solution and delivery.

Preferred:

Experience with multi-tenant SaaS infrastructure, especially per-customer account isolation patterns.

Experience with serverless architecture at scale (hundreds of Lambda functions, DynamoDB single-table design, SQS-based orchestration).

Experience with Datadog or similar observability platforms.

Experience operating self-managed databases on EC2 (MongoDB, Postgres, or similar).

Experience planning and executing production migrations: re-platforming live workloads without downtime or data loss.

Experience working in a regulated environment (HIPAA, SOC 2, PCI, FedRAMP, or similar).

Kubernetes and Helm. Our self-hosted GitHub Actions runners run on EKS via actions-runner-controller.

Familiarity with AWS Organizations, Transit Gateway, RAM (Resource Access Manager).

HDAI is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.