Top Artificial Intelligence DevOps & Platform Engineering Jobs

Work directly with customers to own implementations end-to-end: discovery, integration, deployment, optimization. Write production code, build automations from messy workflows, and serve as the technical face of the company to ensure customer success.

Own and improve Localize’s AWS and Cloudflare infrastructure, databases, platform tooling, deployments, monitoring, security, and SDLC practices. Manage Redis and MongoDB reliability, optimize performance and costs, strengthen CI/CD, lead incident response, support SOC 2 Type II compliance, and maintain disaster recovery capabilities. Partner with product engineers and leadership to prioritize infrastructure improvements, communicate tradeoffs, and improve customer-facing reliability, security, and delivery speed.

Supports the company’s DevOps strategy by designing scalable AWS infrastructure, managing CI/CD processes, integrating engineering workflows, and maintaining GitHub practices. Monitors and troubleshoots production systems, participates in on-call incident response, supports security and compliance, and mentors junior DevOps engineers. The role uses Nomad, Consul, Vault, Terraform, GitHub Actions, Linux, shell scripting, and Python.

Monitor TensorWave’s AI infrastructure across data centers, identify anomalies, perform first-response triage, execute runbooks, document incidents, and escalate issues to engineering or on-site teams. The role supports Kubernetes, GPU, network, storage, and Linux environments; communicates during incidents; contributes to alert tuning and post-incident reviews; and coordinates maintenance activities. This is an on-site rotating 12-hour shift role covering days or nights, including weekends and holidays.

Owns build, test, release, developer productivity, and agent-enabled engineering infrastructure across multi-cloud customer environments. Responsibilities include creating reproducible build systems, release pipelines, software supply-chain security controls, coding-agent workflows, developer self-service tools, observability, alerting, and engineering productivity metrics. Requires strong Python, Linux, container, Kubernetes, GitOps, infrastructure-as-code, cloud, and security expertise, plus leadership of complex projects and migrations.

Build and operate a developer platform for independently versioned modules across global compliance sites. Responsibilities include CI/CD and GitOps automation, reproducible builds, artifact provenance and signing, dependency graph and change-impact tooling, Kubernetes controllers, site provisioning, version management, security patch automation, and large-scale selective test orchestration.

Defines technical strategy for infrastructure reliability and performance, leads complex cross-functional engineering initiatives, mentors engineers, and drives operational excellence. Designs and scales AWS infrastructure, Kubernetes platforms, observability systems, SLOs and SLIs, CI/CD tooling, and infrastructure security. Serves as an escalation point for complex operational issues while influencing architecture and business decisions across the technology organization.

Build, automate, secure, and maintain Google Cloud environments for a federal health customer. Responsibilities include managing Compute Engine, GKE, Cloud Run, networking, IAM, Terraform modules, CI/CD pipelines, monitoring, logging, troubleshooting, and compliance documentation. The role is fully remote and requires support for federal security and operational frameworks.

Build, secure, scale, and maintain cloud infrastructure supporting SaaS products, databases, storage, search, microservices, and machine-learning pipelines. Operate Kubernetes workloads, automate infrastructure with Terraform and Helm, improve reliability and observability, optimize costs, define SLOs and SLAs, participate in incident response and on-call rotations, address vulnerabilities, support customer security integrations, and maintain compliance with SOC 2, HIPAA, and GDPR requirements.

Design and operate AWS cloud infrastructure, improve CI/CD and deployment workflows, build internal platform capabilities, strengthen observability, automate infrastructure, and reduce developer friction. Partner with product teams, participate in incident response and postmortems, maintain Terraform infrastructure as code, support security and compliance controls, and establish scalable operational standards.