Product Engineer II - ArcGIS Monitor

Overview

Do you want to join a team of dynamic and detail-oriented engineers building capabilities that apply AI to simplify and automate enterprise system observability. In this role, you will help define how observability solutions add telemetry and monitor health, performance, and usage of ArcGIS systems.

By observing and analyzing both traditional and cloud infrastructure, software components, and operational metrics, our observability platform helps organizations understand system behavior, detect anomalies, optimize performance, and plan for future capacity across complex ArcGIS deployments.

We are evolving these capabilities to incorporate AI-assisted and agentic operations, enabling administrators to interact with system telemetry using natural language. These capabilities will support system health inquiries, capacity forecasting, root cause analysis, operational planning for maintenance events, and AI-assisted troubleshooting and remediation for enterprise ArcGIS environments.

Responsibilities

• Work with software developers to design, build, test, and release high quality software
• Author and execute test plans; build and manage testing datasets for N-path, acceptance, and regression testing
• Research industry standards and specifications to translate requirements into software design
• Author Scrum user stories that define new feature capabilities to guide the software development process
• Communicate with product users to identify product requirements and advocate for their needs throughout the software development lifecycle
• Collaborate with product UI/UX designers to create mockups of rich user experiences for new capabilities
• Help define user workflows that integrate AI-assisted operations and natural language system interactions for observability and system management
• Evaluate and validate AI-assisted features that support root cause analysis, system diagnostics, performance troubleshooting, and operational recommendations
• Help design and test scenarios that simulate real-world enterprise ArcGIS deployments to validate system insights and recommendations
• Help define safe operational boundaries and human-in-the-loop workflows for AI-assisted system operations and automation
• Author user guide documentation and provide technical review of user guide documentation for accuracy, completeness, and usability
• Provide best practices, user documentation, demonstrations, and technical assistance for the product
• Work with automation engineers to design UI automation

Requirements

• 2+ years of professional experience in a similar position supporting similar responsibilities
• Bachelors in Information Systems (IS), Geographic Information Systems (GIS), Information Technology (IT), Computer Science, or STEM related field
• Experience deploying and/or administering ArcGIS Enterprise, ArcGIS Online, or other comparable IT systems (web / application servers
• Familiarity with traditional RDBMS systems (preferably PostgreSQL), including common SQL commands and concepts
• Familiarity with general server administration on Windows or Linux
• Strong communication and collaboration skills, working in a cross-functional environment
• Excellent problem solving and analytical skills

Recommended Qualifications

• Masters in Information Systems (IS), Geographic Information Systems (GIS), Information Technology (IT), Computer Science, or STEM related field
• Strong testing and QA experience with software products
• Experience maintaining and troubleshooting complex enterprise systems
• Experience with observability systems and performance monitoring concepts (ArcGIS Monitor, Prometheus, Datadog, OpenTelemetry)
• Working knowledge of at least one scripting or programming language (Python, Shell, PowerShell, JavaScript)
• Experience in the SCRUM process and its application to the software development lifecycle
• Familiarity with large language models (LLMs) and their use in developer tools, operational platforms, or observability systems
• Experience with prompt engineering or designing workflows that leverage natural language interfaces
• Understanding of LLM limitations, including hallucinations, context limitations, and reliability challenges
• Interest in building AI-assisted operational systems that help automate diagnostics, troubleshooting, and infrastructure optimization
• Exposure to AI-assisted observability or AIOps concepts
• Experience with software control systems (GIT) and continuous integration and deployment (CI/CD) concepts

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