DontApply.Club
Login Register

AI Platform Engineer

Systems Limited — Jordan · Posted ~2 hours ago

Senior Full-time

Skills

AI platform infrastructure compute provisioning networking IAM CI/CD AI evaluation platforms cost governance capacity planning platform security MLOps LLMOps AI infrastructure cloud infrastructure

🔓 Log in to save this job, tailor your resume & track your apply process — 7 days free, no card needed.

Log in to add to target list

Summary ✨ AI‑Generated

Build and operate the shared platform infrastructure that enables multiple AI teams to deploy models and agents consistently. You will own compute, networking, IAM, deployment tooling, CI/CD standards, evaluation infrastructure, cost governance, capacity planning, and platform security while partnering with MLOps and AI security specialists.

Highlights

Own shared AI platform infrastructure, standardize model and agent deployment, shape platform security and cost governance, and collaborate closely with MLOps and AI security specialists.

Description

We are seeking a AI Platform Engineer with approximately 6–12+ years of experience in the field. Builds and operates the shared AI platform infrastructure — the paved road every AI practice builds on top of, so no team reinvents deployment plumbing. Responsibilities: Build and maintain shared AI platform infrastructure — compute provisioning, networking, IAM for AI workloads Own the internal tooling and templates practices use to deploy models/agents consistently Standardize CI/CD pipelines for AI workloads across practices, including shared AI evaluation platforms Manage platform-level cost governance and capacity planning across concurrent engagements Own platform security posture in partnership with AI Security Engineers Partner with MLOps/LLMOps Engineers on the boundary between platform and workload-specific operations Balance competing infrastructure requests from multiple practice leads Document platform capabilities clearly enough that practices can self-serve Forecast and justify platform spend to non-technical leadership Requirements: 6–12+ yrs platform/infrastructure engineering, with 2+ yrs supporting AI/ML workloads specifically Deep cloud infrastructure expertise (IaC, Kubernetes, networking, IAM), including hosting vector/graph databases Experience building internal developer platforms/tooling, not just running infrastructure Experience integrating and operating managed AI/agentic platforms — Microsoft Azure AI Foundry, AWS Bedrock, and Google Vertex AI — alongside self-hosted open-source stacks as a good-to-have Familiarity with multi-tenant capacity planning and cost allocation Experience with platform-level security hardening Cross-practice stakeholder management — balances competing infra requests from multiple practice leads Cost/capacity planning literacy — can forecast and justify platform spend to non-technical leadership Documents platform capabilities clearly enough that practices can self-serve Collaborative — builds shared infrastructure without becoming a bottleneckSuccess metrics: platform uptime/reliability · cost per workload vs. budget · practice self-service adoption rate