Software Engineer, Infrastructure, AI Labs

Location: New York

## Software Engineer, Infrastructure Apply remote type:
Hybrid:
Work in Office Part-Time locations:
USA-New York-NY-1166 Avenue of Americas:
CAN-Toronto-ON-390 Bay Street, Suite 806time type:
Full time posted on:
Posted Todayjob requisition :
R0034981

At
** Epiq**, your work contributes to complex, global legal outcomes. You’ll join a values‐driven community where integrity guides decisions,
** relentless service
** sets the bar, and we
** thrive on big challenges
** together. We invest in your growth with enterprise‐wide learning and mobility. We celebrate who you are, and we respect life beyond work with flexibility that’s recognized externally. Enabled by modern platforms and AI,
** you’ll do the most meaningful work of your career
** and see your impact at scale.
*
* Job Description:

** Epiq AI Labs is the innovation and engineering hub behind Epiq’s next-generation AI platform for corporate legal departments and global law firms. Operating with the speed and autonomy of a startup and the resources of a global alternative legal services provider, the team builds intelligent agents, reasoning engines, knowledge systems, and structured workflows for litigation, investigations, compliance, and corporate knowledge work.

The team is highly collaborative, deeply technical, and focused on rapid iteration, thoughtful design, and end-to-end ownership.
** The Opportunity
** You will build the cloud infrastructure beneath Epiq AI Labs’ AI platform, spanning infrastructure as code, Kubernetes, CI/CD and release engineering, networking, secrets management, observability, security, and compliance infrastructure. Ownership extends from initial design through production operation.

Infrastructure is treated as a product whose reliability, scalability, and security shape the capabilities of the entire platform. You will partner closely with backend engineering, AI engineering, product management, and security to establish deployment, observability, and security patterns that can scale with the organization.
** Essential

Job Responsibilities
*** Design and implement cloud infrastructure using Terraform, including reusable modules, environment topology, and drift detection and remediation.
* Operate Kubernetes in production, including orchestration, autoscaling, resource governance, network policy, and cluster lifecycle management.
* Build and maintain CI/CD and release infrastructure with progressive delivery, rollback mechanisms, and efficient paths from merge to production.
* Define platform service-level objectives and build the metrics, tracing, alerting, and error-budget practices required to support them.
* Implement security and compliance infrastructure, including hardening, audit logging, data-residency controls, retention, legal hold, and audit evidence collection.
* Build and maintain network, secrets, key, credential, TLS, and certificate-lifecycle infrastructure.
* Contribute to incident response, post-incident review, developer tooling, technical design documentation, architectural review, and platform operational readiness.

Required Qualifications
* 3+ years of experience in infrastructure engineering, platform engineering, or site reliability engineering.
* Demonstrated experience building and operating production infrastructure, including on-call responsibility for systems of your own design.
* Hands-on experience with at least one major cloud platform such as AWS, GCP, or Azure.
* Experience with infrastructure-as-code tools, particularly Terraform, including reusable module design.
* Production Kubernetes experience, including scaling, upgrades, resource limits, network policy, and troubleshooting.
* Ownership of CI/CD pipelines using Git Hub Actions, Azure Dev Ops, or a comparable platform.
* Experience with observability tooling such as Prometheus, Grafana, or Open Telemetry, including defining and maintaining service-level objectives.
* Demonstrated incident-command experience in production environments.
* Experience with secrets and certificate management at organizational scale.
* Proficiency in Python, Go, or a comparable language sufficient to build tooling and automation.
* Strong system-design and architecture…