A productized implementation service that builds and hardens agentic coding workflows for enterprise engineering teams on Google Cloud.
Added Jul 10, 2026
Medium opportunity (72%)
Enterprise engineering teams want agentic developer workflows for refactors, migrations, code review, incident-to-fix loops, and spec-to-PR automation, but the hard part is not demos. They need production-grade pipelines, evaluation harnesses, observability, prompt and agent architecture, and adoption practices that fit their existing engineering standards. Internal platform teams often lack the time or field-tested patterns to move from prototype to reliable daily use.
Start as a forward-deployed implementation service for Google Cloud customers that designs, builds, and validates one concrete agentic developer workflow inside the buyer's repo and CI environment. The delivery includes workflow design, agent/prompt architecture, eval pipelines, observability, rollout playbooks, and reusable modules that can be adapted across teams. Over time, repeated modules become a productized toolkit for spec-to-PR, migration, review, and incident remediation workflows.
Large cloud providers are hiring forward-deployed AI engineers because enterprise buyers are moving from AI experimentation into production agentic systems. Developer AI is especially urgent because refactors, migrations, reviews, and incident fixes are expensive, measurable workflows with clear engineering owners.
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Drive the development and adoption of a modular, and API-first Continuous Delivery ecosystem that unifies policy enforcement, observability, and infrastructure orchestration across all Google environments to accelerate developer velocity, supporting Google's CD tools that handle 154+ million deployments annually across Alphabet. Transform how production incidents are detected, mitigated, and managed, centering the strategy on Autonomous AI agents which will forecast and mitigate potential outage
- Drive measurable impact on Ads builder productivity at scale: code review velocity, deployment frequency, time-to-production, and cross-team coordination overhead for 5,000+ engineers across Ads - Partner with executive stakeholders across Ads organizations to evangelize AI-native development practices, secure shared goals for adoption, and drive the transition from manual coordination to agent-driven orchestration
Agentic-First Development: Lead the transformation of engineering workflows into an agentic-first model, changing how teams develop, test, and ship code autonomously using AI agents.
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