Software Engineering (Mid Level)

Software Engineer (Mid-Level)

Required Qualifications

• 3–5 years of professional full-stack software development experience.
• Strong TypeScript and React experience, including hooks, state management, component composition, and performance optimization for data-heavy interfaces.
• Demonstrated ability to implement UX designs faithfully, with strong attention to spacing, component states, transitions, and interaction details.
• Strong back-end development experience in TypeScript and Python, including building and consuming REST APIs in production.
• Proficiency in relational database design, query development, and query optimization.
• Hands-on experience with a major cloud provider; Azure preferred, including managed compute, storage, API gateway, secrets management, and monitoring services.
• Experience with event-driven architecture, queues, or pub/sub systems for asynchronous processing and result delivery.
• Experience with modern front-end tooling and testing, including build systems, package management, and component or end-to-end testing frameworks.
• Proficiency with Git and branch-based development workflows.
• Understanding of DevOps practices, including CI/CD pipelines, automated testing, and deployment automation.
• Experience with vulnerability management and remediation, including dependency scanning and security patching.
• Strong problem-solving skills and attention to detail.

Preferred Qualifications

• Experience building data-dense professional or analytical interfaces, including large tables, dashboards, filtering, and drill-down workflows.
• Experience with mapping and geospatial visualization libraries.
• Experience with charting and data visualization libraries.
• Familiarity with design tooling and design-system implementation, with the ability to work directly from design files.
• Experience with OpenAPI or Swagger specifications and API documentation tooling.
• Experience with Databricks, Apache Spark, or distributed data-processing platforms.
• Experience integrating machine learning model-serving endpoints into application workflows.
• Experience with containerized deployment and orchestration.
• Experience building multi-tenant SaaS applications with per-tenant isolation.
• Experience using AI-assisted coding tools, such as Cursor or GitHub Copilot, and/or agentic coding tools, such as Claude Code, as part of a professional software-development workflow.

Nice to Have

• Exposure to asset integrity, damage prevention, land management, or stakeholder engagement domains.
• Experience building software where outputs must be auditable and traceable for regulatory purposes.
• Experience with plugin or extension frameworks designed to run third-party code safely.
• Experience with accessibility standards, including WCAG conformance.
• Experience contributing to a shared component library used across multiple products.

Success Metrics

Success in this role will be measured by:

• Shipping interfaces that faithfully match provided UX designs and perform reliably with real-world customer data volumes.
• Delivering reliable, well-documented APIs that other teams can build against independently.
• Delivering end-to-end model configuration and execution workflows for industry, Irth, and customer-supplied models.
• Launching the customer model deployment framework and supporting its adoption by real customers.
• Maintaining interface responsiveness and API performance within established targets under realistic analytical workloads.
• Maintaining a low defect escape rate and ensuring there are no critical unresolved security findings.
• Demonstrating effective collaboration across Design, Data, Model, Product, QA, and Engineering teams.