Technical Lead-Platform Frontend.

Job Openings Technical Lead-Platform Frontend. Apply To Position Use My Indeed Resume Apply Using LinkedIn Who We Are Zinier is building technology for the millions of people who perform critical work in the field every day. Our platform helps field-service organizations in industries such as telecom and energy automate operations, make better decisions, and enable their workforce to work smarter and more efficiently. AI and intelligent automation are increasingly fundamental to how we build our products and how our engineering teams operate. We are looking for engineering leaders who can combine strong software architecture fundamentals with an AI-native approach to building software. What We're Looking For We are looking for a Technical Lead / Senior Tech Lead to lead the architecture and evolution of Zinier's web platform. This is a hands-on technical leadership role responsible for building scalable, high-performance enterprise applications using React, Javascript (Typescript desirable) and Redux, while helping the engineering organization adopt modern AI-assisted and AI-native software development practices. Role Responsibilities Own and evolve the architecture of large-scale frontend applications built primarily using React, TypeScript and Redux/Redux-Saga. Lead and mentor frontend engineers through architecture discussions, design reviews, code reviews and hands-on technical guidance. Design modular, reusable and maintainable frontend architectures capable of supporting complex enterprise workflows. Drive engineering standards around component architecture, state management, API integration, performance, security, accessibility and maintainability. Establish clear patterns for frontend state management using Redux, server-state management, caching and asynchronous data flows. Collaborate closely with Product, UX, Backend, Platform, QA and AI/Data teams to translate complex product requirements into scalable technical solutions. Own major technical initiatives from architecture and prototyping through implementation, production rollout and continuous improvement. Identify and address frontend performance bottlenecks including rendering, memory usage, network performance, bundle size and large-data rendering. Drive modernization of legacy frontend architecture while balancing product delivery and technical debt. Establish engineering practices around automated testing, observability, CI/CD and production reliability. Evaluate emerging frontend technologies and make pragmatic decisions about where they should—or should not—be adopted. Participate in hiring, mentoring and development of engineers and help raise the overall technical bar of the engineering organization. AI-Native Engineering AI should be treated as part of the engineering workflow rather than simply another developer tool. The Technical Lead Will: Drive adoption of AI-assisted software development across design, coding, debugging, testing, documentation and code review. Be proficient with modern AI coding environments and assistants such as Claude Code, GitHub Copilot, Cursor or equivalent tools. Demonstrate the ability to use AI effectively for understanding large codebases, generating and refactoring code, debugging complex problems and accelerating implementation. Establish practices for safely using AI-generated code, including human review, automated testing, security validation and architectural consistency. Use AI to accelerate creation of unit tests, integration tests, E2E tests, test data and regression coverage. Understand concepts such as LLMs, RAG and AI agents sufficiently to collaborate with AI engineering teams and build AI-powered product experiences. Understand how to integrate AI capabilities into web applications through APIs, streaming responses and tool-driven workflows. Continuously experiment with emerging AI engineering capabilities while making pragmatic decisions about their production readiness. Core Technical Experience 8+ years of software engineering experience with significant experience designing and building large-scale frontend applications. Strong hands-on expertise with React and modern React patterns. Strong proficiency in TypeScript and modern JavaScript (ESNext). Deep understanding of Redux, Redux Saga and modern React-Redux patterns. Strong understanding of React Hooks, component composition, rendering behavior, memoization and frontend performance. Strong knowledge of HTML5, CSS, responsive design, browser APIs and modern web standards. Experience designing reusable component libraries and design systems. Strong understanding of frontend architecture patterns including modular architecture, domain-driven frontend design and micro-frontends where appropriate. Experience designing frontend applications that consume REST APIs, GraphQL, WebSockets and event-driven APIs. Understanding of authentication and authorization patterns including OAuth/OIDC, JWT and role-based access control. Strong knowledge of browser performance, caching, network optimization and frontend security. Experience building applications that handle large datasets, complex workflows, real-time updates and highly interactive user interfaces. Understanding of JSON-driven UI engines and configuration-driven architectures, including dynamically rendering UI components, forms, workflows, and behaviors from configuration, is preferred. Modern Engineering Stack & Practices Strong Experience With Several Of The Following: React TypeScript Redux Saga NPM / Yarn Jest React Testing Library Playwright Storybook REST / GraphQL / WebSockets Git and modern branching/development workflows CI/CD using GitHub Actions, Jenkins or equivalent Docker AWS / Azure Application monitoring and observability tools Experience with Playwright or equivalent browser automation frameworks and the ability to drive a strong automated-testing strategy is particularly valuable. Architecture & Platform Thinking The candidate should demonstrate the ability to reason beyond individual features and make architectural decisions involving: Scalability and maintainability Component and design-system architecture Client state vs server state API contracts Performance and rendering strategy Caching Offline/PWA capabilities Security Observability Feature flags Internationalization Accessibility Backward compatibility Incremental modernization of large existing applications The candidate should be comfortable evaluating technologies based on business and architectural requirements rather than adopting frameworks simply because they are new. Additional Skills – Preferred Experience building AI-powered SaaS applications or AI-assisted user experiences. Experience integrating LLM APIs and AI services into production applications. Familiarity with agent frameworks, tool/function calling, MCP or similar emerging AI integration patterns. Experience with Python or Node.js backend development. Experience with cloud-native architectures on AWS or Azure. Experience with server-side rendering, streaming, PWAs or hybrid/mobile applications. Experience with frontend observability and production performance monitoring. Experience modernizing large or legacy React/Redux applications. Experience building configurable enterprise SaaS platforms or low-code/no-code platforms. Contributions to open-source projects or the wider engineering community. Desired Competencies Strong technical depth — able to go from architecture discussions to debugging code when necessary. Architecture ownership — makes pragmatic technical decisions considering scalability, complexity, cost and delivery. Engineering excellence — sets a high bar for code quality, testing, performance, security and maintainability. AI-native mindset — actively looks for opportunities to use AI to improve engineering effectiveness rather than treating AI as an optional productivity tool. Product thinking — understands the customer and business impact behind technical decisions. Ownership — takes responsibility from problem definition through production delivery. Continuous improvement — constantly challenges existing architecture, tooling and development practices. Mentorship — raises the technical capability of engineers around them. Clear communication — can explain complex architectural decisions to technical and non-technical stakeholders. Global collaboration — comfortable working with geographically distributed engineering and product teams. What First 12 Months Looks Like A successful Technical Lead / Architect at Zinier should be able to: Architect it. Build it. Use AI to accelerate it. Test it. Measure it. Improve it. And enable the team to do the same. We are looking for someone who combines strong engineering fundamentals with curiosity about how modern frontend architecture and AI are changing the way enterprise software is built. Apply To Position Use My Indeed Resume Apply Using LinkedIn Role Responsibilities Own and evolve the architecture of large-scale frontend applications built primarily using React, TypeScript and Redux/Redux-Saga. Lead and mentor frontend engineers through architecture discussions, design reviews, code reviews and hands-on technical guidance. Design modular, reusable and maintainable frontend architectures capable of supporting complex enterprise workflows. Drive engineering standards around component architecture, state management, API integration, performance, security, accessibility and maintainability. Establish clear patterns for frontend state management using Redux, server-state management, caching and asynchronous data flows. Collaborate closely with Product, UX, Backend, Platform, QA and AI/Data teams to translate complex product requirements into scalable technical solutions. Own major technical initiatives from architecture and prototyping through implementation, production rollout and continuous improvement. Identify and address frontend performance bottlenecks including rendering, memory usage, network performance, bundle size and large-data rendering. Drive modernization of legacy frontend architecture while balancing product delivery and technical debt. Establish engineering practices around automated testing, observability, CI/CD and production reliability. Evaluate emerging frontend technologies and make pragmatic decisions about where they should—or should not—be adopted. Participate in hiring, mentoring and development of engineers and help raise the overall technical bar of the engineering organization. AI-Native Engineering AI should be treated as part of the engineering workflow rather than simply another developer tool. The Technical Lead Will: Drive adoption of AI-assisted software development across design, coding, debugging, testing, documentation and code review. Be proficient with modern AI coding environments and assistants such as Claude Code, GitHub Copilot, Cursor or equivalent tools. Demonstrate the ability to use AI effectively for understanding large codebases, generating and refactoring code, debugging complex problems and accelerating implementation. Establish practices for safely using AI-generated code, including human review, automated testing, security validation and architectural consistency. Use AI to accelerate creation of unit tests, integration tests, E2E tests, test data and regression coverage. Understand concepts such as LLMs, RAG and AI agents sufficiently to collaborate with AI engineering teams and build AI-powered product experiences. Understand how to integrate AI capabilities into web applications through APIs, streaming responses and tool-driven workflows. Continuously experiment with emerging AI engineering capabilities while making pragmatic decisions about their production readiness. Core Technical Experience 8+ years of software engineering experience with significant experience designing and building large-scale frontend applications. Strong hands-on expertise with React and modern React patterns. Strong proficiency in TypeScript and modern JavaScript (ESNext). Deep understanding of Redux, Redux Saga and modern React-Redux patterns. Strong understanding of React Hooks, component composition, rendering behavior, memoization and frontend performance. Strong knowledge of HTML5, CSS, responsive design, browser APIs and modern web standards. Experience designing reusable component libraries and design systems. Strong understanding of frontend architecture patterns including modular architecture, domain-driven frontend design and micro-frontends where appropriate. Experience designing frontend applications that consume REST APIs, GraphQL, WebSockets and event-driven APIs. Understanding of authentication and authorization patterns including OAuth/OIDC, JWT and role-based access control. Strong knowledge of browser performance, caching, network optimization and frontend security. Experience building applications that handle large datasets, complex workflows, real-time updates and highly interactive user interfaces. Understanding of JSON-driven UI engines and configuration-driven architectures, including dynamically rendering UI components, forms, workflows, and behaviors from configuration, is preferred. Modern Engineering Stack & Practices Strong Experience With Several Of The Following: React TypeScript Redux Saga NPM / Yarn Jest React Testing Library Playwright Storybook REST / GraphQL / WebSockets Git and modern branching/development workflows CI/CD using GitHub Actions, Jenkins or equivalent Docker AWS / Azure Application monitoring and observability tools Experience with Playwright or equivalent browser automation frameworks and the ability to drive a strong automated-testing strategy is particularly valuable. Architecture & Platform Thinking The candidate should demonstrate the ability to reason beyond individual features and make architectural decisions involving: Scalability and maintainability Component and design-system architecture Client state vs server state API contracts Performance and rendering strategy Caching Offline/PWA capabilities Security Observability Feature flags Internationalization Accessibility Backward compatibility Incremental modernization of large existing applications The candidate should be comfortable evaluating technologies based on business and architectural requirements rather than adopting frameworks simply because they are new. Additional Skills – Preferred Experience building AI-powered SaaS applications or AI-assisted user experiences. Experience integrating LLM APIs and AI services into production applications. Familiarity with agent frameworks, tool/function calling, MCP or similar emerging AI integration patterns. Experience with Python or Node.js backend development. Experience with cloud-native architectures on AWS or Azure. Experience with server-side rendering, streaming, PWAs or hybrid/mobile applications. Experience with frontend observability and production performance monitoring. Experience modernizing large or legacy React/Redux applications. Experience building configurable enterprise SaaS platforms or low-code/no-code platforms. Contributions to open-source projects or the wider engineering community. Desired Competencies Strong technical depth — able to go from architecture discussions to debugging code when necessary. Architecture ownership — makes pragmatic technical decisions considering scalability, complexity, cost and delivery. Engineering excellence — sets a high bar for code quality, testing, performance, security and maintainability. AI-native mindset — actively looks for opportunities to use AI to improve engineering effectiveness rather than treating AI as an optional productivity tool. Product thinking — understands the customer and business impact behind technical decisions. Ownership — takes responsibility from problem definition through production delivery. Continuous improvement — constantly challenges existing architecture, tooling and development practices. Mentorship — raises the technical capability of engineers around them. Clear communication — can explain complex architectural decisions to technical and non-technical stakeholders. Global collaboration — comfortable working with geographically distributed engineering and product teams. What First 12 Months Looks Like A successful Technical Lead / Architect at Zinier should be able to: Architect it. Build it. Use AI to accelerate it. Test it. Measure it. Improve it. And enable the team to do the same. We are looking for someone who combines strong engineering fundamentals with curiosity about how modern frontend architecture and AI are changing the way enterprise software is built.