Role Overview
Act as an embedded technical partner to the Locality Experts (LE) team. You will work closely with domain experts to deeply understand operational workflows, identify business gaps, and autonomously design, build, and deploy end-to-end automation and AI tools to eliminate manual bottlenecks.
Acting as a "mini software development team," this unit is responsible for bridging the gap between Map Operations and Google Engineering, with tasks heavily focused on AI model experimentation, generation, and maintenance.
Key Responsibilities
Business Alignment & AI Solution Engineering: Collaborate directly with Locality Experts to gather business requirements and map out operational pain points. Translate domain-specific challenges into technical specifications, and engineer custom Python/AI tools and automated pipelines from prototype to production. Proactively identify opportunities to design, test, and refine AI tools based on Gemini AI models to enhance operations, analysis, and feature generation, optimizing for accuracy and relevance. Integrate AI prompt engineering best practices into automated geospatial workflows.
Configuration & Workflow Enablement: Manage domain issue configurations, configuration files, and run batch issue creation/mutation scripts. Support Geo Mapping Data Technicians by creating and improving configurations to improve daily workflows.
L2 End-to-End Bug Management: Serve as the escalation point for complex churn and policy bugs. Triage and debug complex issues impeding workflows, and resolve and document edge-cases. Take ownership of tracking, tagging, and following up with third-party and Engineering teams to ensure issues are closed systemically.
Engineering Liaison & Tool Documentation: Act as the technical bridge to Engineering. Conduct black-box testing of new tool features and provide detailed feedback. Package validated findings into highly structured formats for Engineering teams, drastically reducing their triage and investigation time. Draft formal Tools Requirements Documents (ORDs), and document and quantify the impact of suggested feature/functionality or infrastructure changes.
Dashboarding, Reporting & Data Interfacing: Design, deploy, and maintain advanced dashboards (e.g., PLX) to track systemic issue clusters, monitor SLA adherence, and generate high-level Root Cause Analysis (RCA) reports. Interface directly with undocumented data (example: GTFS).
Locality Expert Backup: Serve as a functional cross-trained backup to the core Locality Experts team. Step in to support standard policy verification, regional map data auditing, and daily operations whenever critical coverage or bandwidth is needed.
Required Technical Skills (Non-Negotiable)
Programming (3+ Years): Advanced proficiency in Python (specifically for workflow automation, web scraping, and API interactions) and Javascript/Appscript. Must have a solid understanding of data science packages (NumPy, Pandas) and machine learning frameworks (PySpark, TensorFlow).
System & Architecture: Familiarity and ability to read Java and Object-oriented programming. System-level Linux knowledge, including directory setups and debugging.
Database Management & PLX (3+ Years): Expertise in SQL and database querying to manage and manipulate complex spatial/policy datasets. Direct experience building and maintaining PLX dashboards is strictly required.
AI/ML Integration (1–2+ Years): Practical understanding of AI applications, including LLMs, Prompt Engineering, and RAG (Retrieval-Augmented Generation) pipelines to assist in building and deploying autonomous AI agents. Leverage Machine Learning and artificial intelligence output data to continually improve system tooling and workflows.
Geospatial Systems (Highly Preferred): Ability to use GIS skills to support the geo data processing lifecycle from ingestion to submission, including experience with tools like QGIS.
Profile & Experience
3–5 Years of overall professional experience operating within a technical operations, software development, data analysis, or developer support environment.
Preferred: More than one year tenure as a Systems Specialist Tier I.
Possesses a "Product Manager" mindset—able to look at a manual business problem, understand the operational need, and autonomously design a technical solution from prototype to production.
Knowledge of English at least B2 level with strong communication skills and the ability to translate technical concepts into business logic for non-technical stakeholders.
Self-motivated, detail-oriented, and able to work under pressure while finding innovative solutions and improvements.