Senior/Lead Generative AI Platform Engineer

Hybrid 3 days/week in Concord, CA Our client seeks a Senior/Lead Generative AI Platform Engineer to design, implement, and scale enterprise AI/ML platforms across hybrid cloud. The role will architect secure, cost-optimized, and high-performance environments for LLMs and classical ML, spanning compute, storage, networking, and MLOps. The engineer will drive orchestration, observability, and reliability for large-scale workloads while enabling data science through robust tooling and pipelines. Due to client requirements, applicants must be willing and able to work on a w2 basis. For our w2 consultants, we offer a great benefits package that includes Medical, Dental, and Vision benefits, 401k with company matching, and life insurance. Rate: $84.00 to $94.00/hr. w2 JN -032026-105708 #LI-JS1 Responsibilities Design and build scalable AI/ML platform components across on-prem and public cloud environments including GCP, GKE, OpenShift AI (RHOAI), and IBM Cloud Pak for Data for multi-tenant operations. Architect hybrid CPU/GPU grid computing, object and high-performance storage, and low-latency networking to support demanding AI workloads. Deploy and manage enterprise AI tooling including H2O AI platforms (Driverless AI) for automated model development and data virtualization. Implement and administer Run:ai to optimize GPU/CPU utilization with high-throughput and low-latency scheduling for training and inference. Operationalize end-to-end LLM and classical ML pipelines using Vertex AI with CI/CD, automated validation, and observability. Build and maintain vector databases, chunking, and embedding strategies to enable RAG-based applications. Deploy and manage Istio service mesh for secure, observable, and resilient service-to-service and AI API communication. Apply SRE practices including circuit breakers, autoscaling, and reliability patterns to ensure system health. Lead cross-functional architecture discussions and influence platform direction and standards. Experience Requirements 5+ years of Python programming and 3+ years of MLOps experience in production environments. 5+ years with Big Data platforms such as BigQuery or Hadoop and 3+ years with PySpark. 2+ years building APIs, preferably with FastAPI, and integrating with GCP/Azure or API gateways. Expertise with containerization and orchestration including GCP, GKE, Red Hat OpenShift, and Docker with service mesh integration. Hands‑on experience with Vertex AI for pipelines and IBM Cloud Pak for Data for enterprise data management. Strong understanding of LLMs and vector databases, plus working knowledge of AutoML platforms such as H2O Driverless AI or DataRobot. Advanced IaC skills with Terraform, Helm, or Ansible for automating cloud landing zones and cluster configurations. Proficiency in PySpark, Hadoop, or BigQuery for high-throughput data processing and vectorization pipelines. Experience with RAG, prompt orchestration, fine‑tuning, and safety/guardrails (preferred). Deep understanding of GPU/CPU orchestration and high-performance storage for AI workloads (preferred). Ability to lead cross-functional architecture forums and influence senior stakeholders (preferred). Familiarity with Agile methodologies and enterprise project management tools (preferred). #J-18808-Ljbffr