AI Automation Engineer
- Compensation
- Not disclosed
- Location
- Noida, UP, India
- Work setup
- Not specified
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 2+ years
- Category
- Ai engineering
- Posted
Skills
Must have
- Experience: 6+ years in software engineering, test automation, or DevOps, with at least 2+ years dedicated to building AI/ML-assisted developer tooling, LLM integrations, or workflow automation agents
- Flutter & Dart Ecosystem: Deep familiarity with the Flutter framework across Mobile (iOS/Android) and Web, including Dart build systems, DevTools, and native testing toolkits (flutter_test, integratio
- AI / Agentic Tooling: Hands-on experience implementing AI/LLM APIs, prompt engineering, or autonomous workflow agents for code analysis, bug triaging, or test script generation.
- CI/CD & DevOps Automation: Proven track record configuring cloud automation pipelines (GitHub Actions, Google Cloud Build, or GitLab CI) and managing automated release workflows.
- Technical Leadership: Demonstrated success as a senior or lead engineer driving solution architecture, mentoring engineering teams, and leading technical initiatives across distributed client engageme
- Education: Bachelor’s or Master’s degree in Computer Science, Software Engineering, or equivalent practical experience.
Nice to have
- Prior experience working within Google vendor engagements, Buganizer, or Google Cloud infrastructure.
- Experience with static analysis tools, AST (Abstract Syntax Tree) parsing in Dart, or custom linter development.
- Familiarity with mobile device cloud test labs (e.g., Firebase Test Lab) and physical device farm automation.
Full description
SUMMARY
As the Senior AI Automation Engineer for the Flutter Program, you will serve as the technical solution driver for AI-powered automation, workflow optimization, and scalable quality engineering across Google client operations. Operating out of our regional delivery location, you will bridge software engineering, dev tooling, and artificial intelligence to eliminate delivery bottlenecks, accelerate code velocity, and elevate release freshness.
At launch, your focus will be strictly operational and high-impact: building intelligent automation tools for issue triaging, streamlining Pull Request (PR) automation, and guaranteeing SDK/release freshness across multi-platform Flutter builds. As the role matures, you will expand into the program-wide solution architect for AI accelerators, setting technical direction for the delivery center and embedding agentic automation across all active program workstreams.
INITIAL SCOPE & IMMEDIATE PRIORITIES
- Automated Issue Triaging: Architect and deploy intelligent triage tools and LLM/agentic workflows to auto-classify, deduplicate, prioritize, and route incoming Flutter framework and application issues.
- Pull Request (PR) Automation: Develop automated PR review assist bots, static analysis integrations, and continuous regression check triggers to accelerate code review cycles and framework PR merges.
- Release & SDK Freshness: Build automated pipelines to track dependency upgrades, flag breaking changes, validate engine bumps, and ensure continuous freshness across Flutter Web, iOS, and Android builds.
KEY RESPONSIBILITIES
OPTIMIZATION & SCALABILITY
- AI & Agent Infrastructure: Design, implement, and maintain scalable AI automation workflows, test execution platforms, and agentic tools tailored to the Dart and Flutter ecosystem.
- Continuous Integration & Testing Pipelines: Integrate AI automation tools into modern CI/CD systems and physical device testing matrix environments.
- Workflow & Process Optimization: Analyze delivery metrics—such as triage latency, PR cycle time, flakiness rates, and build freshness—and engineer automated solutions to eliminate developer friction.
SOLUTION LEADERSHIP
- Program Solution Driver: Serve as the primary technical authority for AI tooling across all six program workstreams (Design Systems, Issue Repro & Triage, SDK Freshness, Release QA, Framework Bug Fixing, and AI Automation).
- Delivery Location Standard-Bearer: Lead AI adoption and technical capability building within the regional delivery center (Mexico Pod), establishing coding standards, reusable automation assets, and technical blueprints.