Role Overview
The Full-Stack Software Engineer (AI-Assisted) is responsible for building and evolving Inventeer’s product capabilities across backend and frontend—shipping reliable features with clean architecture, strong data modeling, and a consistent user experience.
This is a delivery-focused individual contributor role. You’ll work with the team to implement scalable systems, integrate external APIs, and maintain a high-quality codebase aligned with Inventeer’s standards (repeatable patterns, clear ownership, pragmatic engineering rigor).
A core expectation of this role is the effective use of AI-assisted development tools (such as Claude Code) in day-to-day execution to improve speed, quality, and clarity—without compromising engineering judgment. This role is not about “prompting only”; it is about using AI as leverage inside a disciplined software engineering workflow.
Key Responsibilities
Backend Engineering (Node.js / NestJS)
- Build and maintain scalable backend services using Node.js and NestJS, with focus on performance, reliability, and clean architecture.
- Work with PostgreSQL for data modeling and query design, using Prisma and/or Knex where appropriate for migrations, ORM workflows, and performance-sensitive queries.
- Integrate external APIs to improve product functionality and data flow, with strong error handling, retries, and resilience patterns.
- Write maintainable service logic with clear boundaries, predictable interfaces, and pragmatic abstractions.
Frontend Engineering (React / Vite)
- Build user-facing features using React.js and Vite with attention to usability, responsiveness, and consistency.
- Collaborate on reusable component patterns and frontend architecture that improve delivery speed and maintainability.
- Ensure frontend performance and stability through thoughtful state management and efficient data fetching.
- Implement UI behavior that is clear, predictable, and aligned with product requirements and design direction.
APIs & Data Layer (GraphQL)
- Collaborate on the implementation and evolution of GraphQL APIs using PostGraphile and Apollo (or equivalent tooling).
- Maintain predictable schema design and client integration patterns that support fast iteration and safe changes.
- Improve API ergonomics, query efficiency, and integration reliability as the product scales.
- Help maintain clean contracts between frontend and backend through consistent API practices.
Cloud Integrations & File Management
- Implement file workflows using Google Cloud Storage (uploads, access control, and lifecycle patterns where applicable).
- Build reliable HTTP communication layers using Axios (or equivalent), including timeouts, retries, and structured error handling.
- Contribute to integration patterns that support observability and easier debugging in production environments.
AI-Assisted Engineering Workflow (Claude Code / Equivalent)
- Use AI-assisted development tools in daily work to accelerate implementation, debugging, refactoring, test scaffolding, and documentation.
- Break down tasks into clear, testable units that can be executed efficiently with AI support.
- Critically review, validate, and refine AI-generated code before submission (correctness, security, maintainability, alignment with standards).
- Use AI tools to reduce repetitive work while preserving system understanding and code ownership.
- Document useful prompts/workflows/patterns that improve team velocity and repeatability over time.
Engineering Quality & Collaboration
- Participate in code reviews with a focus on correctness, clarity, maintainability, and shared standards.
- Contribute to documentation, runbooks, and developer-facing notes that reduce ambiguity and rework.
- Collaborate with teammates to unblock delivery and avoid bottlenecks.
- Communicate tradeoffs clearly and escalate risks early when scope, quality, or timelines are at risk.
Required Technical Skills
- Proven production experience with Node.js and React.js.
- Strong full-stack development experience building and shipping real product features end-to-end.
- Solid knowledge of GraphQL, including experience with Apollo, PostGraphile, or equivalent GraphQL tooling.
- Experience with PostgreSQL and relational data modeling, querying, and migrations (Prisma and/or Knex preferred).
- Experience integrating external APIs (authentication, pagination, rate limits, retries, reliability patterns).
- Familiarity with Google Cloud Storage or equivalent cloud file storage systems.
- Strong practice using Axios (or equivalent HTTP client) for efficient requests and error handling.
- Comfortable with Git-based workflows (branching, pull requests, code reviews, commit hygiene).
Required Working Style (AI-Assisted Delivery)
- Comfortable using modern AI-assisted development tools (e.g., Claude Code, Copilot, or equivalent) as part of a professional engineering workflow.
- Strong engineering judgment: able to verify outputs, detect incorrect assumptions, and prevent low-quality automation artifacts.
- Able to move faster with AI without lowering standards.
- Willing to learn and adapt as engineering workflows evolve.
Important: You do not need to be an “AI expert” to apply. We care more about strong software engineering fundamentals, good judgment, and openness to using modern tools effectively.
Nice to Have
- Experience with TDD, unit tests, and practical testing strategies.
- Strong foundations in SOLID principles and common design patterns, applied pragmatically.
- Experience improving developer velocity through reusable patterns, internal tooling, documentation, or automation.
- Exposure to security/compliance-minded engineering (auditability, least privilege, secure defaults).
- Experience working in teams that balance delivery speed with long-term code quality.
- Experience using Claude Code specifically (or similar AI-assisted coding workflows) in production environments.
Behavioral Expectations
- Hands-on execution: You ship. You don’t just discuss architecture—you implement it.
- Ownership & reliability: You take responsibility for the engineering work you commit to and follow through to completion.
- Clarity in communication: You explain tradeoffs clearly, keep PRs readable, and document what matters.
- Quality without gold-plating: You balance speed and rigor—strong fundamentals, minimal drama.
- AI with accountability: You use AI to increase leverage, but you remain accountable for the final result.
- Team-first delivery: You collaborate, review thoughtfully, and help the team move faster over time.
What Success Looks Like in This Role
In the first months, a strong hire in this role will:
- Ship reliable full-stack features consistently
- Contribute clean code and useful reviews
- Use AI-assisted workflows to improve speed without introducing quality regressions
- Reduce rework through better implementation discipline and clearer documentation
- Strengthen the team’s repeatable engineering patterns over time