Senior, Platform Engineer

Overview

Senior people-manager role leading the platform engineering team that runs the Enterprise AI platform estate (Google Cloud data and AI services, AI coding tools, Accelerator platform), applying SRE principles, vendor management and infrastructure-as-code.

What you'll do

• Run the Google Cloud and SaaS platforms Enterprise AI uses to build AI solutions, including BigQuery, Vertex AI, GKE or Cloud Run, and the Accelerator platform, ensuring availability, security and cost efficiency.
• Own Google Cloud platform architecture, designing and operating BigQuery and Vertex AI environments including partitioning, reservations and cost controls, plus Pub/Sub and Dataflow ingestion and Cloud Composer orchestration.
• Apply SRE principles: service-level objectives, observability (Cloud Monitoring, OpenTelemetry), capacity planning and vendor incident escalation across the platform estate.
• Use AI coding assistants as the default mode of work and build automations that handle routine platform tasks at scale.
• Manage the platform estate through Infrastructure-as-Code (Terraform, GitOps, CI/CD) so configurations are versioned, auditable and reproducible.
• Treat platform users as customers by delivering self-service capabilities, clear documentation and fast onboarding for FDEs, FSEs and data scientists.
• Embed security, data privacy and AI governance controls so AI solutions inherit compliance, and set the Google Cloud security baseline (IAM and least-privilege access, Cloud KMS (CMEK), VPC Service Controls, Secret Manager, Organization Policies).
• Act as technical counterpart to strategic SaaS and cloud vendors (Microsoft, Anthropic, Databricks, Google) on roadmap, capacity, integration and incident escalation, and lead the Google Cloud relationship for data and AI services.
• Continuously evaluate emerging AI tooling, piloting promising options through sandbox proofs of concept and making adoption or deferral decisions.
• Build and maintain reusable platform components so delivery roles do not reinvent the wheel across engagements.
• Lead and develop the platform engineering team by hiring, setting objectives, running 1:1s and performance reviews, and developing junior engineers toward greater platform ownership.
• Track and report AI tooling adoption against organisational adoption goals, and manage platform budget and cloud cost (FinOps) across Google Cloud and SaaS spend.
• Own team delivery and prioritisation, setting the team's roadmap and prioritising platform work against delivery-team needs.

What you'll need

• Overall 15 years of professional experience.
• At least 8 years of experience running SaaS or cloud platforms in a production setting.
• Strong proficiency in Python and SQL.
• Hands-on experience with Infrastructure-as-Code (Terraform), GitOps and modern CI/CD.
• Hands-on production experience with Google Cloud data and AI services (BigQuery, Vertex AI, GKE or Cloud Run, Pub/Sub, and IAM).
• Daily use of AI coding agents (Claude Code, Codex, GitHub Copilot, Databricks AI Assistant) as a primary development mode.
• Experience operating production services with SLOs and on-call practices.
• Experience managing or leading engineers, including hiring, performance management and development.
• Bachelor's degree in Computer Science, Software Engineering, or equivalent practical experience.

Nice to have

• Experience running AI or ML platforms specifically: SaaS Accelerators, AI coding tool estates, integration platforms, or analytics-AI tools.
• Experience as the technical counterpart to strategic SaaS and cloud vendors, managing roadmap, capacity and incident escalation.
• Experience building agents and automation against operations workflows.
• Familiarity with regulated industry constraints (GxP, including 21 CFR Part 11, GDPR and SOX) and how to embed them into platform controls.
• Google Cloud Professional certification (Professional Cloud Architect, Professional Data Engineer, or Professional Machine Learning Engineer). Azure or other cloud certifications are also valued.
• Master's degree in Computer Science, Distributed Systems, or SRE is advantageous.

Details

• Location: Bengaluru, Luxor North Tower.