Full Stack Engineer

What We Do CarParts.com is the go-to eCommerce platform for auto care and maintenance. We provide drivers with quality parts at competitive prices and enable them to schedule appointments with trusted mechanics directly through our website. Using world-class design principles and the latest technologies, we deliver a fast, intuitive digital experience backed by our company-owned national distribution network. What We Do CarParts.com is the go-to eCommerce platform for auto care and maintenance. We provide drivers with quality parts at competitive prices and enable them to schedule appointments with trusted mechanics directly through our website. Using world-class design principles and the latest technologies, we deliver a fast, intuitive digital experience backed by our company-owned national distribution network. With over 1,000 employees worldwide, we are scaling rapidly, fueled by our most recent strategic partnership and $35 million investment. This positions us for the next phase of growth as we continue to empower drivers along their journey. Our Culture At CarParts.com, our culture goes beyond our core values of Safety First, Customer Focused, and Commitment to Excellence. We are a performance-driven, data-focused, and fast-paced team where results matter and winning is expected. Hungry & Hardworking: We set ambitious goals, measure progress with clear metrics, and hold ourselves accountable to deliver results. Promote from Within: We reward top performers with opportunities for growth and advancement. Collaborative & In-Person: We believe the best ideas and fastest execution happen face-to-face. High Standards: We move quickly, pay attention to details, and dig deep - whether it’s analyzing contracts, aggregating complex scenarios, or building clear, data-driven presentations. No Passengers: We value grit, ownership, and the relentless pursuit of results We are investing heavily in AI-powered engineering — building intelligent agents, integrating LLMs into our platform, and developing MCP (Model Context Protocol) servers to orchestrate context-aware automation across our ecommerce stack. This role sits at the intersection of full-stack engineering and applied AI. Why This Role Is AI-Forward Role This is not a traditional full-stack role with AI bolted on. AI is woven into how we build, ship, and operate: Every engineer uses AI coding assistants (Claude Code, Claude Cowork, GitHub Copilot, Cursor) as a daily multiplier — not an optional extra We are building production AI agents that automate merchandising, search relevance, customer support triage, and content generation Our agents use agentic patterns — autonomous planning, multi-step reasoning, tool orchestration, self-correction, and human-in-the-loop checkpoints — not simple prompt-response chains Our platform exposes MCP servers so LLM-powered tools can read catalog data, trigger workflows, and act on real-time signals We treat prompt engineering and token economics as first-class engineering disciplines, reviewed in PRs alongside application code If you want to ship AI features that millions of customers interact with — not just prototype in a notebook — this is the role. Who You Are The Builder: You’d rather write a reusable abstraction, a CLI tool, or a code generator than repeat the same manual task twice — and you design systems that scale without you babysitting them. The Troubleshooter: A user reports a broken checkout flow and you instinctively open the network tab, trace the API call, and pinpoint whether it’s a frontend state bug, a backend validation edge case, or a data mismatch — before anyone else finishes reading the ticket. The AI Enthusiast: You treat token budgets and prompt design with the same rigor as component architecture — optimising context windows, evaluating model trade-offs, and shipping AI-powered features that move product metrics. What You’ll Do Build & Ship Product Features (50%) Design, develop, and own full-stack features across React/Next.js frontends and Node.js/Express microservices Build AI-powered product experiences: intelligent search, personalized recommendations, automated content generation, and conversational commerce flows Design and develop agentic systems — agents that plan, reason over multiple steps, select and call tools, handle errors autonomously, and escal Implement agentic patterns:ReActloops, chain-of-thought planning, reflection/self-critique, memory (short-term context and long-term retrieval), and multi-agent coordination Develop and maintain MCP servers that expose ecommerce domain tools (catalog, pricing, inventory, order) to LLM-powered clients Integrate LLM APIs into production paths with proper error handling, fallback strategies, andcostguardrails Write prompts, evaluation harnesses, and monitoring for AI features — treat them as code, version them, review them AI & Automation Requirements & Developer Experience (30%) Optimize frontend performance: Core Web Vitals, page load time, time-to-first-byte Design APIs (REST,OpenAPI) that are clean, well-documented, andbackward-compatible Build shared tooling: CLI utilities, code generators, reusable component libraries, and internal developer tools powered by AI Improve CI/CD pipelines, containerized builds, and deployment workflows Participate in architecture decisions, code reviews, and technical design documents 1+ year hands-on experience integrating LLM APIs (OpenAI, Anthropic, or equivalent) into production or near-production systems Demonstrated ability to build or extend AI agents that use tool-calling, function execution, and structured output Proven approach to token budget management: prompt optimization, caching strategies, cost monitoring dashboards Collaborate & Grow (20%) Translate business requirements into technical designs with product and design stakeholders Mentor engineers on AI integration patterns, prompt engineering, and modern full-stack practices Stay current with AI/ML tooling, LLM advances, and MCP ecosystem developments — bring what you learn back to the team Position Requirements Contributions to open-source AI tooling or MCP ecosystem CarParts.com is an equal-opportunity employer. We enthusiastically accept our responsibility to make employment decisions without regard to race, religious creed, color, age, sex, sexual orientation, national origin, religion, marital status, medical condition, physical or mental disability, military service, pregnancy, childbirth and related medical conditions, or any other classification protected by federal, state, and local laws and ordinances. The above-noted job description is not intended to describe, in detail, the multitude of tasks that may be assigned but rather to give the incumbent a general sense of the responsibilities and expectations of his/her position. As the nature of business demands change so, too, may the essential functions of this position. Core Engineering (Required) 5+ years of experience in full-stack web application development using Node.js, JavaScript, TypeScript, and modern frameworks Extensive experience building scalable applications and microservices using React, Next.js, Node.js, Express, HTML, and CSS Hands-on TypeScript across frontend and backend systems Strong knowledge of RESTful API design andOpenAPIspecifications Experience designing and integrating APIs, including REST and modern data-fetching patterns Extensive experience with MySQL, MongoDB, PostgreSQL, and Redis, with solid understanding of data modeling trade-offs Familiarity with micro-frontend architecture and module federation Strong experience building performant React applications using hooks and state management (Redux or equivalent) Experience with cloud-native development using Docker and containerized environments Experience with CDNs, caching strategies, performance optimization, and security considerations Strong knowledge of JavaScript build tools (Webpack, Vite, or modern bundlers) Proficiency with Chrome DevTools and frontend performance profiling Experience with SPA, PWA, responsive design, and MPA architectures Strong foundation in data structures, algorithms, and database design Proven experience in software architecture, design patterns, and engineering best practices AI & Automation (Required) 1+ year hands-on experience integrating LLM APIs (OpenAI, Anthropic, or equivalent) into production or near-production systems Demonstrated ability to build or extend AI agents that use tool-calling, function execution, and structured output Solid understanding of agentic concepts and design patterns: ReAct(Reason + Act) loops, chain-of-thought planning, and step-by-step task decomposition Tool orchestration — selecting, invoking, and chaining external tools based on model reasoning Memory architectures: conversation context, scratchpads, vector-backed long-term recall Self-correction and reflection — agents that detect errors in their own output and retry Human-in-the-loop checkpoints, confidence thresholds, and graceful fallback to manual workflows Multi-agent coordination — delegating subtasks across specialized agents and merging results Acquaintance or hands-on experience developing agents: Built, extended, or shipped at least one agent (production, internal tool, or well-scoped prototype) that performs multi-step autonomous tasks Familiar with agent frameworks such asLangChain,LangGraph,CrewAI,Autogen, Claude Agent SDK, or custom orchestration loops Comfortable designing agent tool schemas, managing agent state, and debugging non-deterministic agent behavior Experience designing or contributing to MCP servers or similar context-orchestration layers Proven approach to token budget management: prompt optimization, caching strategies, and cost monitoring Comfortable using AI coding assistants (GitHub Copilot, Claude Code, Claude Cowork, Cursor) daily to accelerate development Able to write effective prompts for code generation, refactoring, test creation, and documentation Understands foundational LLM concepts: tokens, temperature, context windows, embeddings, and RAG Can evaluate AI-generated code for correctness, security, and performance — not just accept output blindly Nice to Have Experience with public cloud services (AWS, Azure, GCP) Experience with e-commerce/retail purchase journeys Experience migrating legacy applications to modern stacks Familiarity with vector databases (Pinecone,Weaviate,pgvector #J-18808-Ljbffr