软件工程师(中级)
Software Engineering (Mid Level)
软件工程师(中级)
地点:远程(美国)
部门:洞察(AI/ML)
汇报对象:工程经理
职位简介
Irth 正在构建一个基于 AI 的威胁和风险管理系统,用于管道资产完整性。该平台整合了三种此前从未在同一位置共存的能力:
- 基于 Databricks 和 Azure 的受控、跨产品数据平台。
- 由 AI 驱动的数据摄入层,可在无需大量服务支持的情况下对客户数据进行标准化、修复和增强。
- 可重复使用的分析层,可对这些数据运行行业标准、Irth 自研以及客户自建的风险模型。
我们正在寻找一位中级全栈应用软件工程师,负责构建操作员使用的界面以及其背后的系统。
前端方面,你将使用 TypeScript 和 React 构建生产级应用程序,将 UX 设计转化为直观、可靠的界面,忠实反映设计意图。
后端方面,你将使用 TypeScript 和 Python 构建连接应用程序与数据平台和分析层的 API 和服务。
你的工作将包括:
- 配置模型和威胁参数的界面。
- 运行分析模型并返回结果的执行路径。
- 显示风险评分和支持证据的地图和仪表板视图。
- 允许客户在平台上部署和运行自己模型的服务和框架。
你将加入一个这些界面正在定义而非维护的阶段,这为你提供了塑造产品及其技术基础的重要机会。
我们的用户是基于密集技术信息做出重要决策的完整性工程师。因此,前端体验更接近于构建复杂的专业应用,而不是传统的营销页面。
主要职责
1. 前端开发 —— 主要职责
- 使用 TypeScript 和 React 构建生产级用户界面,忠实实现布局、交互行为和视觉细节中的 UX 设计。
- 从设计文件和原型入手;在实现前与设计师沟通识别并提出差距、边缘情况和模糊点,而不是默默做假设。
- 构建模型配置和威胁选择体验,包括:
- 多步骤流程
- 参数表单
- 输入验证
- 清晰的错误和恢复状态
- 构建数据密集型界面,包括:
- 可排序和过滤的表格
查看英文原文
Software Engineer (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 Responsibilities
1. 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
- Dashboards
- Drill-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 Functions
- API 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
- Templates
- Input 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 APIs
- Monitor, 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
Requirements
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.
Benefits
Benefits
- Competitive Salary – A competitive compensation package based on experience and qualifications.
- Medical, Dental, and Vision Insurance – Comprehensive insurance coverage to support you and your family.
- 401(k) Plan with Company Match.
- Generous Paid Time Off (PTO) – Time off to support work-life balance and personal needs.
- Company-Paid Holidays – Paid holidays throughout the year.
- Flexible Work Options – Work-from-home opportunities are available, depending on role and business needs.
- On-Call Compensation – Additional pay for eligible on-call shifts.
Originally posted on Himalayas