AI Platform Architect / ML Ops Architect

AI Platform / AI Ops Architect
Location: Chicago, IL (or nearby states)
Experience: 10+ Years

We are seeking an experienced AI Platform / AIOps Architect to lead the design, implementation, and governance of enterprise-scale ML and LLM platforms on Google Cloud. This role requires a strong blend of architecture expertise, MLOps leadership, cloud-native engineering, and AI platform strategy.

What You''ll Bring

<>AI Platform & MLOps Expertise

• 10+ years of experience in AI/ML platform engineering, MLOps, or AI infrastructure roles with significant architectural responsibility.
• Deep understanding of end-to-end machine learning lifecycles, including data ingestion, feature engineering, model development, deployment, monitoring, governance, and continuous improvement.
• Experience building and managing enterprise-grade MLOps platforms and frameworks.

<>Google Cloud & AI Ecosystem

• Strong hands-on expertise with Google Cloud''s AI and ML services, including:
  • Vertex AI
  • Vertex AI Pipelines
  • Feature Store
  • Model Registry
  • Model Monitoring
  • BigQuery ML
  • Google Kubernetes Engine (GKE)
  • Cloud Functions
  • AutoML
  • API Gateway
  • Cloud-native CI/CD services
• Experience designing scalable AI solutions using cloud-native Google Cloud Platform services and modern containerized architectures.

<>ML Engineering & LLMOps

• Practical experience with tools such as MLflow, Kubeflow, Airflow, BentoML, KServe, Seldon, and related ML platform technologies.
• Experience supporting or implementing LLMOps capabilities, including prompt management, evaluation frameworks, experimentation tracking, and deployment automation.
• Familiarity with foundation models and generative AI ecosystems such as Vertex AI Foundation Models, OpenAI, Anthropic, and Llama.

<>Data & Platform Engineering

• Strong SQL expertise and experience working with modern data platforms including Snowflake, Databricks, Spark, and related analytics technologies.
• Experience designing feature engineering pipelines and managing feature stores at scale.
• Knowledge of reproducibility and governance practices, including lineage tracking, metadata management, version control, and model traceability.

<>Development & Operations

• Strong Python programming skills and experience building cloud-native applications.
• Experience implementing automated ML pipelines covering training, testing, validation, deployment, monitoring, and model promotion.
• Hands-on knowledge of monitoring and observability solutions including Cloud Monitoring, Prometheus, Grafana, and Vertex AI Model Monitoring.
• Strong understanding of cloud security, IAM, secrets management, compliance controls, and artifact governance.

Key Responsibilities

• Define and drive the overall MLOps strategy while ensuring alignment with program objectives and delivery milestones.
• Design, build, and maintain scalable ML and LLM operational pipelines covering training, deployment, monitoring, governance, and lifecycle management.
• Lead the development of container-based AI platforms leveraging GKE and related orchestration technologies.
• Establish governance frameworks for model management, prompt versioning, evaluation processes, and operational monitoring of LLM-powered applications.
• Create reusable architecture patterns, standards, and best practices that can be leveraged across multiple customer and internal initiatives.
• Implement comprehensive observability solutions for AI systems, including drift detection, auditability, lineage tracking, and operational monitoring.
• Partner with data engineering, DevOps, platform engineering, and business stakeholders to deliver production-ready AI solutions.
• Drive architecture reviews, provide technical leadership, and resolve complex platform and deployment challenges.
• Ensure adherence to enterprise security, governance, and compliance requirements across all AI and ML workloads.
• Mentor engineering teams and promote adoption of modern MLOps, AI platform, and cloud engineering best practices.