Platform Engineer

HHAeXchange is the leading technology platform for home and community-based care. Founded in 2008, HHAeXchange was born out of an idea to create a fully comprehensive end-to-end homecare solution to help people who are aging or have disabilities thrive in their homes and communities. Our employees are passionate about transforming the healthcare space by building the only homecare ecosystem that fully connects patients, personal care providers, managed care organizations, and states.

HHAeXchange is seeking a Platform Engineer to join our Data & AI Engineering team. Reporting to the Director of Analytics, this role sits at the intersection of platform reliability and delivery automation – ensuring the infrastructure that powers our AI platform, data pipelines, and internal applications is stable, scalable, and continuously improving.

This is a hands-on engineering role embedded within a team building Layer 1 of HHAeXchange’s AI Platform – the core machinery that enables AI-powered capabilities across the organization. The engineer will own the reliability and deployment lifecycle of that infrastructure, working closely with AI Platform Engineers and Data & AI Engineers to operationalize everything we build on AWS.

As our AI platform matures and internal tooling expands, this role becomes the connective tissue between development velocity and production stability – ensuring that what gets built gets shipped reliably, monitored proactively, and scaled confidently.

To perform this job successfully, an individual must be able to perform each essential job duty satisfactorily with or without reasonable accommodation. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

Position is remote for candidates located within the EST or CST time zones within the US.

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Essential Job Duties
Platform Reliability (SRE)

Own availability, latency, and performance targets for AI platform services and data infrastructure running on AWS

Design and implement monitoring, alerting, and observability frameworks across the platform stack

Lead incident response, root cause analysis, and post-mortem processes for platform-level outages or degradations

Define and track SLOs/SLAs for core platform primitives including RAG pipelines, agent orchestration services, and model access layers

Proactively identify reliability risks and drive engineering improvements before they become production issues

Build and maintain runbooks, disaster recovery procedures, and operational documentation

DevOps & Delivery Automation

Design, build, and maintain CI/CD pipelines for AI platform components, data pipelines, and internal applications

Own infrastructure-as-code (IaC) practices across the team using tools such as Terraform or AWS CDK

Manage and optimize AWS environments including ECS, Lambda, S3, RDS, Redshift, API Gateway, and related services

Implement and enforce security, compliance, and cost optimization best practices across AWS infrastructure

Automate deployment, scaling, and configuration management to reduce manual operational overhead

Partner with AI Platform Engineers to containerize and operationalize AI services and agent frameworks

Support Data & AI Engineers with environment management, access controls, and deployment tooling for Polaris and data pipeline infrastructure

Cross-Team Enablement

Serve as the operational backbone for the AI platform team – ensuring engineers can ship and iterate quickly without being blocked by infrastructure concerns

Contribute to our “factory model” vision by making deployment and reliability a repeatable, scalable capability rather than an ad hoc function

Other Job Duties

Other duties as assigned by supervisor or HHAeXchange leader.

Travel Requirements
Travel up to 10%, including overnight travel

Required Education, Experience, Certifications and Skills

3+ years of professional experience in a DevOps, SRE, or platform engineering role

Hands-on AWS experience required – AgentCore, Bedrock, ECS, Lambda, S3, RDS, Redshift, CloudWatch, IAM, VPC, and related services

Experience with infrastructure-as-code tools such as Terraform or AWS CDK

Strong CI/CD experience with tools such as GitHub Actions

Experience with containerization and orchestration (Docker, ECS, or Kubernetes)

Familiarity with AI/ML infrastructure patterns – model serving, vector databases, pipeline orchestration (strongly preferred)

Experience with observability and monitoring tooling (Datadog, CloudWatch)

Prior experience in a SaaS environment

Strong verbal and written communication skills with ability to collaborate across technical and non-technical stakeholders

Self-starter with a proactive approach to identifying and resolving infrastructure risk before it impacts delivery

Willingness to explore and adopt AI tools responsibly to enhance productivity and innovation in your role.

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The base salary range for this US-based, full-time, and exempt position is $110,000-120,000/yr, not including variable compensation. An employee’s exact starting salary will be based on various factors including but not limited to experience, education, training, merit, location, and the ability to exemplify the HHAeXchange core values.

This is a benefits-eligible position. HHAeXchange offers competitive health plans, paid time-off, company paid holidays, 401K retirement program with a Company elected match, including other company sponsored programs.

HHAeXchange is an equal-opportunity employer. The Company offers employment opportunities to all applicants and employees without regard to race, color, religion, national origin, sex, sexual orientation, gender identity or expression, age, disability, medical condition, marital status, veteran status, citizenship, genetic information, hairstyles, or any other status protected by local or federal law.