Platform Architect, AI/ML Infrastructure, GCP-focused

Job not on LinkedIn

🔥 0 minutes ago

🌐 Brazil, Argentina, +3 more countries – Remote

🇧🇷 Brazil – Remote 🇦🇷 Argentina – Remote 🇨🇴 Colombia – Remote 🇲🇽 Mexico – Remote 🇵🇪 Peru – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🔙 Backend Engineer

👻 Ghost score 16%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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PrideLogic

WebsiteLinkedInAll Job Openings

11 - 50 employees

PrideLogic is a company that does not currently have detailed information available as their website is under construction. More details may be provided in the future once updates are made available on their site.

📋 Description

• Build and operate model and inference serving infrastructure for real-time and batch inference across multiple tenants • Manage latency, throughput, autoscaling, and reliability • Own the ML deployment lifecycle, including model registry, versioning, promotion workflows, canary/shadow/A-B rollouts, and rollback • Operate agentic and LLM workloads in production, including providers, gateways, quotas, throttling, guardrails, prompt/version management, and graceful degradation • Build reproducible training, evaluation, and deployment pipelines as code with lineage and reproducibility • Extend Terraform infrastructure-as-code patterns to ML systems and multi-project designs • Operate GitOps for ML workloads using ArgoCD configuration and promotion workflows • Run ML and AI workloads on multi-tenant GKE, managing GPU scheduling, workload placement, tenant isolation, and cost-aware capacity • Own ML reliability and observability, including inference SLOs, model/data drift detection, regression monitoring, alert quality, on-call ergonomics, and runbooks • Drive ML cost efficiency through accelerator right-sizing, committed-use and Spot VM capacity, and tenant/workload cost attribution • Use agentic coding tools to scaffold environments, generate/review IaC and pipeline code, and accelerate automation • Identify platform problems proactively and shape platform evolution

🎯 Requirements

• 5+ years in platform engineering, SRE, MLOps, or infrastructure, including meaningful time operating production systems at scale • Hands-on experience deploying and operating ML or AI workloads in production • Strong SRE/DevOps foundation, including ownership of production reliability, SLOs, post-mortems, and measurable improvements • Deep Terraform expertise, including complex state, reusable modules, multi-project configurations, and CI-driven plan/apply workflows • Strong GitOps background with ArgoCD or Flux in production • Deep Kubernetes knowledge, including production cluster operations, failure modes, and control-plane understanding • Production GKE experience is strongly preferred • Strong GCP background: VPC networking, Compute Engine, IAM, Cloud Storage, and multi-project/organization design • Hands-on production experience with BigQuery, including partitioning, clustering, query cost/performance tuning, and dataset-level IAM • Familiarity with Dataflow, Pub/Sub, or Dataproc • Hands-on experience building and operating CI/CD pipelines, including understanding of ML pipeline differences • Senior-level automation-first approach • Active use of agentic coding tools • Strong written and verbal communication • Bachelor's degree or equivalent experience in IT or Computer Science indicated in application questions • Ability to work EST time zone • Preferred experience with GPU/accelerator scheduling, LLM inference at scale, ML orchestration, model registries, drift monitoring, FinOps, data infrastructure, multi-tenant infrastructure, and startup-to-enterprise scaling

🏖️ Benefits

• Payment in USD • Remote work arrangement in LATAM • Working hours aligned with EST time zone