We're Hiring: Junior AI-Native Builder (Vibe Coder)
Job Title: Junior AI-Native Builder (Vibe Coder)
Location: Remote Department: Engineering / AI-Native Product
Reports To: Head of AI Engineering / CTO
Job Type: Contract
- About the Company
Envizien is a bespoke software development and innovation studio committed to building future-proof digital solutions for visionary organizations. We combine world-class engineering, human-centered design, and AI-accelerated development tools to deliver scalable, secure, and elegant products that stand the test of time.
As a boutique development house, we partner closely with our clients, which include global talent development companies, education organizations, and purpose-driven enterprises, to architect, design, and build custom technology that supports their long-term growth. We take pride in deeply understanding each client's mission, culture, and goals so we can create digital experiences and systems uniquely tailored to their needs.
Our global, high-performing team brings together expertise across product strategy, UX design, full-stack engineering, AI-integration, cloud architecture, and quality assurance. This allows us to build software that isn't just functional, but meaningful, intuitive, durable, and adaptable to the ever-changing landscape of technology.
Envizien is grounded in craftsmanship, curiosity, and excellence. Whether developing enterprise platforms, mobile applications, internal systems, or AI-powered tools, we ensure every solution is thoughtfully engineered, culturally aligned, and built to evolve.
Our mission is simple: Create technology that empowers people, elevates organizations, and shapes a better future… one product at a time.
- Role Summary
The Junior AI-Native Builder, sometimes called a "vibe coder," is a new kind of role for a new kind of engineering. You are the person who uses AI-powered development tools (Lovable, Replit, Base44, Bolt, v0, and the tools that will replace them next year) to turn product ideas into working software faster than traditional engineering allows. You pair those tools with backing infrastructure (Supabase, Airtable, and the connective tissue that turns a prototype into something real) to ship functional products in hours or days rather than weeks.
This is a genuinely new discipline. Three years ago the role didn't exist. Today it's changing the economics of early-stage product development. Five years from now, the people who got good at it early will be setting the standards for how the industry works. Envizien is hiring junior AI-native builders specifically because we want to grow the people who will shape this discipline, not hire people who have already peaked in it.
This is not a traditional junior developer role. You will not spend your first year writing loops in a language nobody uses anymore. Instead, you will learn to direct AI tools with precision, prompt well, iterate fast, debug what the AI produces, and know when to step outside the tools and write code yourself. You will learn to build with Supabase, Airtable, Stripe, and the other services that make AI-generated prototypes actually work. You will learn to ship, get feedback, and iterate with a speed that would have been impossible in traditional software development a few years ago.
You will partner closely with senior engineers, designers, product managers, and the studio's AI engineering team to take client concepts from "what if" to "here's a working version you can try." You will be mentored by people who care about your growth. You will be given real work, real feedback, and progressively harder assignments as you demonstrate readiness. What you build here will set up the rest of your career in a field that is forming in real time.
The ideal candidate is early in their career but serious about it. You are curious by nature, comfortable with ambiguity, fast with new tools, and hungry to build real skill in a discipline that doesn't yet have textbooks. You are motivated by the opportunity to learn at a studio that takes this new craft seriously, not just by the title or the stack.
- Key Responsibilities
3.1 Rapid Prototyping with AI-Powered Builders
3.1.1 Build functional prototypes and minimum viable products using AI-powered development platforms (Lovable, Replit, Base44, Bolt, v0, Cursor, and the tools that emerge next). 3.1.2 Translate product briefs, wireframes, and conversations into working software, focusing on the shortest path between idea and something a human can actually click. 3.1.3 Iterate fast. A vibe coder who spends three days polishing a prototype has missed the point. The goal is to learn what's right by building, not by planning. 3.1.4 Know the strengths and failure modes of each AI-powered tool well enough to pick the right one for each job, and to know when none of them fit.
3.2 Backing Infrastructure and Data
3.2.1 Connect prototypes to real data and state using Supabase, Airtable, Firebase, or equivalent services, so the products you build behave like real products rather than static mockups. 3.2.2 Design data models that are simple enough to ship fast but structured enough that they don't become a refactor tax the moment the product gets real. 3.2.3 Integrate third-party services (Stripe for payments, Resend for email, ElevenLabs for voice, Claude or OpenAI for AI features, Zapier or Make.com for automation) to turn prototypes into functional end-to-end systems. 3.2.4 Build a working understanding of authentication, user management, and the basic security hygiene that keeps even a prototype from becoming an embarrassment.
3.3 AI Tool Fluency and Judgment
3.3.1 Develop real skill with the prompts, workflows, and iterative patterns that get good output from AI-powered builders. Prompting is a craft. Treat it that way. 3.3.2 Debug what the AI produces, including the moments when the generated code is wrong, insecure, inefficient, or subtly broken in ways the tool doesn't warn you about. 3.3.3 Know when to stay inside the AI tool and when to open the code yourself to fix what the tool can't. The best vibe coders aren't afraid of code. They just don't write it when they don't have to. 3.3.4 Stay current on the AI-powered development ecosystem, which is changing faster than any other discipline right now, and bring new tools and patterns back to the team.
3.4 Shipping and Iteration
3.4.1 Ship working prototypes to stakeholders quickly, even when they are rough, so feedback can shape the next iteration instead of speculation driving the first version. 3.4.2 Set up hosting, deployments, and basic observability for the prototypes you ship using the tools that fit (Vercel, Netlify, Railway, Supabase's built-in deployment, or the platform's native hosting). 3.4.3 Gather feedback from real users (or stand-in users) and translate it into the next iteration, with the discipline to separate strong signal from noise. 3.4.4 Know when a prototype has done its job. Some prototypes prove a concept and then get thrown away. Some evolve into real products. Both outcomes are valid. Knowing which is which matters.
3.5 Collaboration and Communication
3.5.1 Work closely with senior engineers, designers, and product managers to understand what each prototype is supposed to prove and to shape it toward that goal. 3.5.2 Collaborate with the AI engineering team on prototypes that involve LLM features, learning the evaluation and reliability discipline that separates a flashy demo from a real AI product. 3.5.3 Participate in standups, design reviews, and retrospectives with the honesty that helps the team improve, including flagging when a tool isn't working or when a prototype is in trouble. 3.5.4 Communicate clearly in writing, including project updates, prototype walkthroughs, and the "how this works" explanations that let stakeholders understand what you've built.
3.6 Learning and Growth
3.6.1 Build your skills actively. This field has no textbooks yet. Your growth depends on you reading what's being written, trying what's new, and learning from the senior engineers around you. 3.6.2 Begin learning adjacent skills as your foundation strengthens: the real programming concepts behind the AI-generated code, database design, API design, and the engineering practices that turn prototypes into products. 3.6.3 Learn the products you build deeply enough to understand not just how they work, but why they were designed the way they were, and where their real quality risks live. 3.6.4 Take feedback seriously. The fastest growth in a new field comes from senior engineers pointing out what you missed or could have done better, and from you actually absorbing it.
3.7 Execution Discipline and Reliability
3.7.1 Maintain a steady rhythm of shipping, reviewing, and iterating, honoring commitments within the timelines that rapid prototyping demands. 3.7.2 Keep your project organization, documentation, and handoffs clean even when moving fast. Speed is not an excuse for chaos. 3.7.3 Respect the line between "prototype" and "production." A prototype that needs to become a real product eventually needs real engineering. Know when to call that moment. 3.7.4 Own your focus time. Good building requires concentration. Know when to defend it.
- Qualifications
4.1 Required
4.1.1 Demonstrated interest and hands-on experience with AI-powered development tools (Lovable, Replit, Base44, Bolt, v0, Cursor, or similar), through personal projects, bootcamp work, freelance gigs, or professional experience. Even if it's not on a resume, you've been building. 4.1.2 Working familiarity with at least one backing infrastructure service (Supabase, Airtable, Firebase, or equivalent) and the ability to explain what it does and why you'd use it. 4.1.3 Basic coding literacy in at least one language (JavaScript, TypeScript, Python, or similar) sufficient to read, edit, and debug what AI tools generate. You don't need to be a fluent coder, but you can't be afraid of code. 4.1.4 Strong curiosity and self-direction. This field changes every few months. A vibe coder who waits to be taught has already fallen behind. 4.1.5 Solid product instincts. You can look at a half-finished prototype and know what's missing, what's broken, and what's not worth fixing yet. 4.1.6 Excellent written communication. You can explain what you built, how it works, and what's still rough in a way stakeholders can actually use. 4.1.7 High reliability and ownership. When you commit to shipping a prototype, the team can count on it being shipped. 4.1.8 Comfortable working in a remote, high-autonomy environment with the self-discipline to manage your own focus and workload. 4.1.9 Genuine hunger to grow in a new field. You are not applying for this role to coast.
4.2 Preferred
4.2.1 A portfolio of personal or freelance projects built with AI-powered development tools, even small ones. We care more about what you've shipped than where you went to school. 4.2.2 Early exposure to traditional full-stack development (React, Next.js, Node.js, Python) that gives you the foundation to understand what the AI tools are generating. 4.2.3 Familiarity with prompt engineering for code generation, including the patterns that produce good output consistently versus the patterns that produce hallucinations. 4.2.4 Experience integrating LLM APIs (Claude, OpenAI, Google) into applications, even at a basic level. 4.2.5 Working knowledge of design tools (Figma) sufficient to translate a designer's vision into a working prototype. 4.2.6 Experience with no-code automation tools (Zapier, Make.com, n8n) and a clear-eyed view of where they help and where they don't. 4.2.7 Background in product management, design, or business strategy that predates your coding work, giving you instincts that many engineers lack. 4.2.8 Active participation in the AI-native builder community, including Twitter, Discord, Reddit, Indie Hackers, or wherever the conversation is happening this month. 4.2.9 Exposure to databases and SQL sufficient to understand what's happening under the hood of Supabase or Airtable.
4.3 Growth Potential
4.3.1 This role exists because AI-native development is a new discipline and Envizien wants to grow the people who will shape it. This is not a dead-end role. You will be paired with senior engineers and AI engineering mentors who will help you grow into more substantial roles over time. Paths from here include AI-Native Product Engineer, Full-Stack Developer, AI Engineer, or a deeper path into product management, depending on where your interests and strengths lead. What you get out of this role depends on what you put in. The studio will match your hunger with opportunity.
- Core Values (PHHSX)
The following values are how we evaluate fit, performance, and behavior. They are not aspirational. They are the working standard for this role and every role at Envizien, even at the junior level, and they matter especially in a new field where formal credentials don't yet exist.
5.1 P, Passionate: You are genuinely excited by AI-powered development and what it makes possible. You build things for fun. You try the new tool the weekend it comes out. Your passion shows in the small details: the side project you shipped last month, the prompt pattern you discovered on your own, the prototype you built because you wanted to see if you could.
5.2 H, Humble: You know this field is new, which means nobody is an expert yet, including you. You ask questions freely. You listen when a senior engineer explains why the AI-generated code you shipped has a security issue. You credit the teammate who helped you understand something you didn't get the first time. You treat your early lack of depth as something to fix rather than hide.
5.3 H, Hungry: You don't wait to be taught. You look up the concept you don't recognize. You try the tool you haven't used. You read the Twitter thread, the Discord conversation, the Substack post that explains the new pattern. You ask for harder projects when you're ready for them. You measure your growth against where you want to be in two years, not where the job description asks for today.
5.4 S, Smart (People-Smart): You can raise a concern with a senior engineer without making them defensive, explain why a prototype matters to a product manager, and receive feedback on your own work without getting discouraged. You read the room. You know when to push on a technical choice and when to defer to someone more experienced.
5.5 X, X-Factor: You execute reliably, without excuses. When you commit to shipping a prototype, you ship it. When the AI tool produces something broken, you don't blame the tool. You fix it, learn from it, and ship anyway. When the work is rough around the edges, and rapid prototyping work often is, you bring the same care to the hundredth iteration as you did to the first.
- Why This Role Matters
AI-native development is changing how software gets built. The studios and companies that figure this out first will have a serious advantage over the ones who treat it as a curiosity. A single AI-native builder, pointed at the right problem, can produce in a week what used to take a team a quarter. That is not a minor efficiency gain. It's a structural shift in how early-stage product work happens, and it's happening right now.
This role matters because Envizien intends to be one of the studios that figures this out first. You are not joining to run errands for senior engineers. You are joining to help shape how the studio builds in a discipline that doesn't yet have best practices. The prototypes you ship will help clients see what's possible. The patterns you discover will feed into how the team operates. The mistakes you make will teach the studio something real, because you'll be among the first people on the team doing this work.
This role also matters because every senior AI-native builder at Envizien five years from now will have started as a junior one somewhere. You are not just doing today's prototypes. You are building the foundation of a career in a field that is being invented in real time. What you learn in this role will compound for a decade.
You will do this work in a place that takes the craft seriously, that invests in the growth of the people who do it, and that treats junior builders as future leaders rather than cheap labor. You will be mentored by engineers who genuinely want you to grow. You will be given real work and real feedback. You will be trusted to ship things that matter.
If that's the kind of role you've been looking for, where a new craft meets real growth in a studio that will actually invest in you, we want to hear from you.
Send through your CV to this email: subscriptions@envizien.com