Generative AI Engineer

Arkhya Tech. Inc.; Bellevue (WA); On-site; USD 138,000 - 248,000; Full time

Job summary

Arkhya Tech. Inc. is seeking a Senior/Lead Generative AI Platform Engineer to lead design, implementation, and scaling of enterprise-grade AI/ML and Generative AI platforms.

The role focuses on building secure, scalable infrastructure across hybrid cloud environments, leveraging GCP, GKE, OpenShift AI, Docker and Kubernetes, with an emphasis on MLOps, GPU/CPU resources, and advanced data tooling.

Qualifications

• 5+ years Python development.
• 3+ years production MLOps.
• 5+ years Big Data experience with BigQuery and/or Hadoop.
• 3+ years PySpark experience.
• 2+ years API development, preferably FastAPI.
• Strong hands-on experience with GCP, GKE, OpenShift, Docker, and Kubernetes.
• Experience with Vertex AI and IBM Cloud Pak for Data.
• Knowledge of LLMs, Vector Databases, RAG, and Generative AI platforms.
• Experience with Terraform/Helm/Ansible.

Responsibilities

• Design and build scalable AI/ML platforms across on-prem and public cloud environments.
• Architect hybrid-cloud environments using GCP, GKE, Red Hat OpenShift AI, and IBM Cloud Pak for Data.
• Design CPU/GPU compute, storage, networking and infra strategies for AI workloads.
• Implement Run:ai for efficient GPU/CPU scheduling and resource utilization.
• Build and operationalize MLOps pipelines using Vertex AI, CI/CD, automated validation, and observability.
• Design and maintain Vector Databases, embeddings, chunking strategies, and RAG pipelines.
• Deploy and manage Istio Service Mesh for secure observability of microservices.

Skills

Python development

MLOps

Big Data (BigQuery/Hadoop)

PySpark

API development (FastAPI)

GCP/GKE/OpenShift/Kubernetes

Vertex AI

LLMs/Vector DBs/RAG

Terraform/Helm/Ansible

Tools

Run:ai

Vertex AI

IBM Cloud Pak for Data

GCP

GKE

OpenShift

Docker

Kubernetes

Terraform

Helm

Ansible

Job description

We are looking for a highly experienced Senior/Lead Generative AI Platform Engineer to lead the design, implementation, and scaling of enterprise-grade AI/ML and Generative AI platforms.

Location: Concord, CA

Work Model: Hybrid

Employment Type: Contract

Experience: 12+ Years

Role Overview

The ideal candidate will have strong experience across AI/ML platforms, MLOps, hybrid cloud, Kubernetes, GCP, GPU/CPU infrastructure, and Generative AI. This role will bridge infrastructure and data science while building secure, scalable, and high-performance platforms for ML and LLM workloads.

Key Responsibilities

• Design and build scalable AI/ML platforms across on-prem and public cloud environments.
• Architect hybrid-cloud environments using GCP, GKE, Red Hat OpenShift AI, and IBM Cloud Pak for Data.
• Design CPU/GPU compute, high-performance storage, networking, and infrastructure strategies for AI workloads.
• Implement Run:ai for efficient GPU/CPU scheduling and resource utilization.
• Build and operationalize MLOps pipelines using Vertex AI, CI/CD, automated validation, and observability.
• Design and maintain Vector Databases, embeddings, chunking strategies, and RAG pipelines.
• Deploy and manage Istio Service Mesh for secure and observable microservices communication.
• Implement SRE practices, autoscaling, reliability patterns, and operational best practices.

Required Skills

• 5+ years of Python development experience.
• 3+ years of production MLOps experience.
• 5+ years of Big Data experience with BigQuery and/or Hadoop.
• 3+ years of PySpark experience.
• 2+ years of API development, preferably FastAPI.
• Strong hands-on experience with GCP, GKE, OpenShift, Docker, and Kubernetes.
• Experience with Vertex AI and IBM Cloud Pak for Data.
• Strong understanding of LLMs, Vector Databases, RAG, and Generative AI platforms.
• Experience with H2O Driverless AI, DataRobot, or similar AutoML platforms.
• Strong Infrastructure as Code experience with Terraform, Helm, or Ansible.

Preferred Skills

• Experience with LLM/GenAI platforms, including RAG, prompt orchestration, fine-tuning, safety, and guardrails.
• Strong understanding of GPU/CPU orchestration and high-performance storage.
• Experience with Run:ai, Istio, and enterprise Kubernetes environments.
• Ability to lead architecture discussions and influence senior stakeholders.
• Experience working in Agile enterprise environments.
• If you have strong hands-on experience building and scaling enterprise AI/ML platforms and Generative AI infrastructure, we would like to hear from you.