Software Engineering (Mid Level)

Location: Remote (US)

Department: Insights (AI/ML)

Reports to: Engineering Manager

About the Role: Irth is building a new AI-driven threat and risk management platform for pipeline asset integrity. The platform brings together three capabilities that have never previously lived in one place at Irth:

• A governed, cross-product data platform built on Databricks and Azure.
• An AI-powered ingestion layer that normalizes, repairs, and enriches customer data without services-heavy onboarding.
• A reusable analytical layer that runs industry-standard, Irth-developed, and customer-built risk models against that data.
• We are seeking a mid-level, full-stack Application Software Engineer to build both the interfaces operators use and the services behind them.
• On the front end, you will build production applications in TypeScript and React, translating UX designs into intuitive, reliable interfaces that faithfully reflect the intended design.
• On the back end, you will build APIs and services in TypeScript and Python that connect the application to the data platform and analytical layer.
• Your work will include:
• Interfaces for configuring models and threat parameters.
• Execution paths that run analytical models and return results.
• Map and dashboard views that surface risk scores and supporting evidence.
• Services and frameworks that allow customers to deploy and run their own models on the platform.
• You will join at a point where these interfaces are being defined rather than maintained, giving you meaningful opportunity to shape the product and its technical foundation.
• Our users are integrity engineers making consequential decisions based on dense, technical information. The front-end experience is therefore closer to building a sophisticated professional application than a traditional marketing surface.
• Key Responsibilities1. Front-End Development — Primary Responsibility
• Build production user interfaces in TypeScript and React, implementing UX designs faithfully across layout, interaction behavior, and visual details.
• Work from design files and prototypes; identify and raise gaps, edge cases, and ambiguities with designers before implementation rather than making assumptions silently.
• Build model configuration and threat-selection experiences, including:
• Multi-step workflows
• Parameter forms
• Input validation
• Clear error and recovery states
• Build data-dense interfaces, including:
• Sortable and filterable result tables
• DashboardsDrill-down experiences from system to segment level
• Map-based visualization of risk across pipeline geometry
• Design interfaces for long-running analytical operations, providing meaningful progress indicators, partial results, and recovery from failures.
• Build reusable, well-typed components and contribute to a consistent component library and design-system implementation.
• Ensure responsive behavior, accessibility, and cross-browser compatibility across applications.2. Back-End & API Development
• Design and build REST APIs in TypeScript and Python for model configuration, execution, and results retrieval.
• Establish clear API contracts, versioning strategies, and maintainable service boundaries.
• Build execution and orchestration services for analytical workloads, including:
• Long-running jobs
• Status tracking
• Result persistence
• Failure handling and recovery
• Implement event-driven and asynchronous patterns so analytical results can be delivered without blocking the user interface.
• Design and implement database schemas and queries across the application data store and lakehouse serving layer.
• Integrate with Databricks and Azure services, including:
• Model serving endpoints
• Azure Storage
• Azure FunctionsAPI Management
• Container-hosted services
• Write and maintain OpenAPI specifications and ensure interactive API documentation remains accurate as contracts evolve.3. Customer Model Deployment Framework
• Build the end-to-end experience that allows customers to deploy, configure, and execute their own models within product workflows, across both front-end and back-end systems.
• Implement connection and data-mapping workflows, including:
• Guided wizards
• TemplatesInput validation
• Customer-supplied data mapping
• Build results-integration capabilities so customer model outputs can be displayed and aggregated alongside industry and Irth model outputs.
• Implement isolation and governance controls to ensure customer-deployed code runs safely within appropriate tenant boundaries.4. Quality, Security & Performance
• Write automated tests across the stack, including:
• Component and interaction tests on the front end
• Unit tests on the back end
• Integration tests across services and APIsMonitor, troubleshoot, and optimize application responsiveness and API performance under realistic analytical workloads.
• Implement authentication, authorization, and tenant isolation using the platform's identity and secrets-management services.
• Identify, assess, and remediate security vulnerabilities in application code, infrastructure integrations, and dependencies.
• Participate in code reviews and contribute to CI/CD pipelines and deployment automation.5. Collaboration
• Partner closely with Design on feasibility, interaction details, edge cases, and design-system consistency.
• Work with data engineers and data scientists to define clear interfaces between application, data, and model layers.
• Partner with Product and QA on requirements, edge cases, acceptance criteria, and release readiness.
• Contribute to:
• Technical and design reviews
• Architecture and decision records
• Engineering standards
• Reusable development practices