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AI Platform Engineer
Job in
Long Beach, Los Angeles County, California, 90802, USA
Listed on 2026-06-06
Listing for:
Carparts.com
Full Time
position Listed on 2026-06-06
Job specializations:
-
IT/Tech
Systems Engineer, AI Engineer
Job Description & How to Apply Below
What We Do
is the go-to eCommerce platform for auto care and maintenance. We provide drivers with quality parts at competitive prices and enable them to schedule appointments with trusted mechanics directly through our website. Using world-class design principles and the latest technologies, we deliver a fast, intuitive digital experience backed by our company-owned national distribution network.
With over 1,000 employees worldwide, we are scaling rapidly, fueled by our most recent strategic partnership and $35 million investment. This positions us for the next phase of growth as we continue to empower drivers along their journey.
We've built Axle - 's domain AI platform and winner of the MACH Alliance Impact Award for Best Multi-Agent Ecosystem - and we're expanding it. This role is central to that expansion.
Our Culture
At , our culture goes beyond our core values of Safety First, Customer Focused, and Commitment to Excellence. We are a performance-driven, data-focused, and fast-paced team where results matter and winning is expected.
* Hungry & Hardworking:
We set ambitious goals, measure progress with clear metrics, and hold ourselves accountable to deliver results.
* Promote from Within:
We reward top performers with opportunities for growth and advancement.
* Collaborative & In-Person:
We believe the best ideas and fastest execution happen face-to-face.
* High Standards:
We move quickly, pay attention to details, and dig deep - whether it's analyzing contracts, aggregating complex scenarios, or building clear, data-driven presentations.
* No Passengers:
We value grit, ownership, and the relentless pursuit of results
THE OPPORTUNITY
One exceptional engineer. AI as the team.
This is not a standard Dev Ops posting. We are looking for one unusually capable, AI-native engineer to own our entire platform engineering and SRE function - using autonomous agents, LLM-powered pipelines, and MCP-based tooling as force multipliers to do the work of a team, on-site, in close partnership with our engineering leadership.
You will inherit a mature, fully containerized AWS estate (9 EKS clusters, 27 accounts, 228 Kubernetes nodes), an Akamai CDN layer managing live traffic splits, Git Hub Actions + Jenkins CI/CD pipelines for a Webpack 5 micro-frontend monorepo, and an operational AI agent platform - Ops Whisperer - already in production monitoring 25 AWS accounts with a 91% autonomous resolution.
Your job is to extend all of it, automate what remains manual, and be the person who makes every deployment, incident, and infrastructure change happen with speed, precision, and intelligence.
SCOPE OF OWNERSHIP
What you'll own
AWS Multi-Account Infrastructure
* EKS clusters across dedicated AWS accounts
* EC2 worker nodes via Auto Scaling Groups
* SQS pipelines
* AWS Bedrock (Claude) for AI agent workloads
Kubernetes & Containerization
* EKS clusters
* Node group mgmt
* Kops clusters alongside EKS
* Multiple environment tiers with full blast-radius isolation
CI/CD & Release Management
* Multiple Repos
* Git Hub Actions workflows + Jenkins pipeline management
* Turbo build system across multiple micro-frontend packages
* Canary release gating and rollback automation
CDN & Traffic Management
* Akamai Property Manager config
* Phased Release Cloudlet for Canary and Production split
* Security, Throttling and Monitoring
* Jenkins-driven cache invalidation
Observability & Incident Response
* Elastic/Kibana
* Cloud Watch across all AWS accounts
* Business performance monitoring
* SQS backlog + pipeline health alerting
* On-call ownership, proactive, AI-assisted triage
NON-NEGOTIABLE
The AI-native expectation
This is a role where AI fluency is not a bonus - it is how you do the job. We expect you to build, operate, and improve autonomous agents that handle monitoring, alerting, triage, and routine operational work. You are not just a consumer of AI tools; you are the person who builds them, deploys them into production, and iterates on them based on real operational data.
You will extend Ops Whisperer(AI Platform and Observability agent), contribute to the Axle platform, build MCP servers that give agents new capabilities, and apply LLM-powered reasoning to…
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