Google Cloud & AI Platform Architect - Remote

Salary: $83,000 - 123,000 per year Requirements:

• Bachelors degree in computer science or a related field, or equivalent applicable work experience.
• 10+ years of experience in software development or architecture, including at least 3 years of individual-contributor technical leadership in platform or architecture roles.
• Deep knowledge of AI/ML ecosystems and experience designing enterprise-scale MLOps pipelines and AI Ops frameworks.
• Strong expertise in Google Cloud Platform and cloud-native architecture, with hands-on knowledge of GCP services and patterns for AI/ML platforms, MLOps, and CI/CD.
• Experience with multi-agent architecture, including orchestration patterns, tool or skill registries, memory and state management, and agent observability.
• Experience establishing technical standards and coordinating distributed engineering teams.
• Proven ability to lead platform architecture with cross-functional engineering partners and deliver enterprise-scale AI platform solutions.
• Ability to navigate novel technologies and ambiguity in evolving domains.
• Familiarity with security and compliance standards for platform operations.
• Strong analytical and problem-solving skills, with a data-driven approach.
• Excellent communication, program coordination, and stakeholder engagement skills, including presenting technical concepts to senior leaders and non-technical audiences.

• Translate enterprise AI strategy into actionable platform roadmaps and technical priorities, balancing immediate needs with long-term scalability and reliability.
• Partner with data, cloud, security, infrastructure, product, engineering, and data science teams to define and deliver end-to-end AI architecture and operational strategies.
• Evaluate emerging technologies, platform options, and buy-versus-build decisions; recommend enhancements and optimize cost and performance.
• Design, implement, and scale cloud-based infrastructure on Google Cloud Platform and Databricks for internal and external applications.
• Architect AI/ML platform components, including data pipelines, model training and inference, orchestration, continuous training, deployment, monitoring, and observability.
• Establish architecture practices, patterns, standards, and controls for AI/ML development and deployment; ensure designs meet enterprise, regulatory, governance, privacy, and responsible AI requirements.
• Participate in Scale-lane Architecture Review Board decisions, advising on infrastructure fit, serving readiness, and cost-per-unit implications.
• Guide agentic platform evolution in partnership with the AI Architect Principal and AI Solution Architects, aligning work with organizational priorities and technology roadmaps.
• Mentor and coach AI architects, engineers, and AI Ops engineers through design reviews, technical guidance, and reusable patterns.
• Provide hands-on technical leadership, conduct design reviews, and uphold standards for code quality, testing, documentation, and maintainable engineering practices.
• Lead team development activities, including career growth, technical upskilling, performance reviews, hiring, onboarding, and team building.
• Oversee platform scalability, reliability, security, and cost optimization across cloud and on-premises environments.
• Implement monitoring and observability tools; define and track performance metrics such as uptime, latency, and resource utilization.
• Build and execute architecture audits, identify automation and process-improvement opportunities, and address platform performance issues and outages.
• Lead incident response and post-incident reviews, and apply relevant emerging technologies and industry practices to improve platform resilience and efficiency.

• AI
• Architect
• CI/CD
• Cloud
• Databricks
• GCP
• MLOps
• Model Training
• Security
• Support
• Model Serving

More:

We are hiring a Senior Architect, Google Cloud Platform & AI Platform Architect, for Ultas AI Architecture pod to lead the scale lane for our core AI platforms. This is a senior architecture role with at least half of the work focused on hands-on platform design, infrastructure decisions, MLOps patterns, reviews, and standards. The role works across teams to shape platforms that are scalable, performant, reliable, and cost-efficient, while also providing technical mentorship and team leadership.

last updated 41 week of 2026