• Develop, maintain, and implement new features across the Shopify Headless storefront, focusing on key pages (homepage, PDP, PLP, cart, and checkout) using React, HTML, Tailwind, SCSS, and TypeScript. • Implement and customize Shopify Functions to extend backend logic and commerce behavior • Integrate the storefront with external services and APIs, including the Shopify Storefront API (GraphQL), Shopify Admin API (GraphQL), Shopify Metafields, and third-party integrations like Algolia. • Act as an engineering partner to UX/UI designers, translating Figma designs into pixel-perfect, performance-optimized, and robust React components, while actively contributing to design critiques to ensure technical feasibility and component reusability early in the product lifecycle. • Customize existing Shopify themes and apps to meet business needs • Contribute to the evolution and governance of our Storybook-based design system, including architecting new, high-quality React components, establishing comprehensive usage guidelines, and maintaining the source of truth for design tokens across the application. • Optimize storefront performance with lazy loading, proper asset management, and code splitting • Ensure cross-browser compatibility and mobile responsiveness • Uphold the highest standards of web accessibility, ensuring compliance with WCAG 2.1 AA. • Debug and resolve technical issues related to front-end development and theme code • Maintain and follow coding best practices and documentation standards

• Develop and maintain scalable frontend applications using React and modern JavaScript frameworks. • Build reusable, high-quality UI components and ensure a consistent user experience across the platform. • Integrate frontend applications with REST or GraphQL APIs to consume and manage data efficiently. • Work with Headless CMS platforms (ideally Sanity) to manage and render dynamic content. • Collaborate closely with designers, backend developers, and product teams to implement new features and improvements. • Optimize applications for performance, responsiveness, and cross-browser compatibility. • Participate in code reviews, ensuring best practices, code quality, and maintainability. • Contribute to the continuous improvement of the frontend architecture and development processes.

• Design and implement features using Angular, React, and TypeScript that meet performance, accessibility (a11y), and SEO objectives. • Collaborate with product and design teams to translate requirements into technical designs and estimates. • Write clean, testable code and maintain a component-based design system. • Contribute to architecture and non-functional requirements (scalability, security, observability). • Improve site speed and Core Web Vitals metrics by optimizing bundling, rendering strategy, and caching.

Role Description We are hiring a highly execution-focused Senior Technical Developer (Contract) to own the technical and systems layer of an enterprise project controls platform. Our software replaces the messy spreadsheet-and-email toolchain that dominates megaproject oversight with a single production-live system serving major capital construction programs. Because our data directly informs client decisions worth millions of dollars, absolute data accuracy and system reliability are core table stakes. This role is ideal for an implementation partner with expert-level TypeScript and React fundamentals who wants to step directly into a production codebase and build out real-world ML/AI infrastructure (including fine-tuned LLMs and voice interactive pipelines)—not just wrap basic APIs. You will work directly with the founder in an environment completely free of ticket theater and management layers. Work Model: Remote | Contract Time Commitment: 25–40 hours / week Timezone Requirement: EST/CST Compensation: Open What You’ll Own - Act as the primary implementation partner working directly in a production codebase. - Own the building, engineering, and feature deployment of full-stack system features. - Design, implement, and submit clean Pull Requests (PRs) for review. - Build and maintain robust machine learning pipelines, covering training data preparation, fine-tuning scripts, and system evaluations. - Write complex raw PostgreSQL database schemas, queries (CTEs, window functions), and data migrations. - Develop, scale, and optimize high-throughput model inference steps and custom voice pipelines (STT/TTS). - Decompose feature briefs, propose structural technical architectures, and autonomously resolve backend production bugs. Experience - 3+ years of production experience with strict TypeScript/JavaScript (generics, type inference, discriminated unions). - Production React experience with clear ownership over shipping and maintaining real, live web applications. - Next.js App Router literacy, demonstrating deep familiarity with server vs. client components, middleware, and route handlers. - SQL Fluency with raw PostgreSQL; you must have zero dependency on an ORM. - Python proficiency explicitly tied to data preparation, training, and evaluation for machine learning pipelines. - Strict Git workflow discipline, maintaining clean commits and structural code review habits. - Familiarity or deep learning trajectory inside ML infrastructure frameworks (personal projects, fine-tuning experiments, or coursework). Skills - Strong independent research skills to learn unfamiliar technical stacks and specialized domains without hand-holding. - Excellent written English communication skills for documentation, thorough code reviews, and technical notes. - High technical agency to fill the gaps given an ambiguous brief, proposing sensible fallback paths independently. - Meticulous attention to detail: you test your own edge cases and ensure work is right the first time. Nice-To-Have - Hands-on PyTorch and Hugging Face model fine-tuning (PEFT/LoRA, Transformers library). - Voice/speech ML engineering background (STT, TTS, or end-to-end voice pipeline tuning). - GPU infrastructure management capabilities (self-hosted GPU servers, CUDA, resource monitoring). - Front-end data visualization expertise (Tailwind CSS, Radix unstyled primitives, complex dashboard trend charting). - Automated document report generation systems (PDF, Excel, Word exports). - DevOps exposure: Docker containerization, multi-stage builds, and automated CI/CD pipelines. - Prior domain exposure to capital construction, industrial software, or engineering project controls. Success Metrics - Day 30: Local environment completely running, 5–8 production PRs successfully merged, full data tracing verified from the database to the UI, and basic domain familiarity achieved. - Day 60: Autonomously implementing core features, writing raw SQL migrations confidently, handling active production bugs, and launching initial LLM fine-tuning experiments. - Day 90: Decomposing broad feature briefs into standalone technical tasks, proposing architecture modifications, showing full-stack comfort, and actively contributing to voice AI and ML infrastructure pipelines. Why This Role Stands Out - Fully remote flexibility across global talent pools. - Direct impact on enterprise assets: Your code directly influences active capital construction programs worth millions of dollars. - Production ML experience: Opportunity to fine-tune LLMs, build real voice pipelines, and manage GPU inference server clusters on actual running systems, not simple demo tools. - Specialized domain depth: Gain high-value expertise in a specialized, multi-billion dollar industrial sector that most developers never get to touch. - Modern, zero-bloat stack: Build with fresh, current tools applied to complex engineering problems without corporate ticket theater or management bottlenecks. How to Apply - Apply with a brief introduction (2–3 paragraphs) explaining your technical background and why this specific intersection of full-stack engineering and ML infrastructure stands out to you. - Links to your active work (GitHub, technical portfolios, or production application code examples). - Your availability profile (Earliest start date, target rate expectations, weekly hours capacity, and timezone location).