Platform Engineer

HHAeXchange

12d•$110,000 - $120,000•Remote

About The Position

HHAeXchange is seeking a Platform Engineer to join their Data & AI Engineering team. This role focuses on platform reliability and delivery automation, ensuring the infrastructure for their AI platform, data pipelines, and internal applications is stable, scalable, and continuously improving. The engineer will be responsible for the reliability and deployment lifecycle of the infrastructure, working with AI Platform Engineers and Data & AI Engineers to operationalize solutions on AWS. This role acts as a crucial link between development speed and production stability, ensuring reliable shipping, proactive monitoring, and confident scaling of AI platform components. The position is remote for candidates in the EST or CST time zones within the US.

Requirements

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.

Nice To Haves

Familiarity with AI/ML infrastructure patterns – model serving, vector databases, pipeline orchestration

Responsibilities

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.
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.
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 duties as assigned by supervisor or HHAeXchange leader.