AI-Native Software Architect — Senior Full-Stack IC

Location: Remote — Philippines
Schedule: Part-time initially, with a path to full-time
Working hours: Full overlap with Los Angeles/Pacific Time working hours
Starting compensation: $7–$12 USD per hour, based on experience
Reports directly to: Founder and CEO

Executive Summary

Bellaura is seeking an experienced AI-Native Software Architect who can personally architect and ship production features at exceptional speed using tools such as Codex and Claude. This is a hands-on senior individual-contributor role for someone who can translate business requirements into technical architecture, direct AI development workflows, and ensure the resulting software is secure, maintainable, tested, and production-ready. The role can expand substantially in scope, compensation, and ownership as the company grows and becomes funded.

The Opportunity

Bellaura is an early-stage technology platform for creators, creative professionals, events, collaboration, and bookings. You will work directly with a technical founder and a team that includes experienced Microsoft engineers.

Much of the application has been developed through AI-assisted engineering. We are now looking for someone with deep software-engineering experience who can dramatically increase our development velocity without sacrificing quality.

This is not a traditional architect role focused on diagrams, meetings, or managing other engineers. You will make architectural decisions and personally implement major features using AI as an engineering multiplier.

What You Will Do
Translate business and product requirements into clear technical requirements.
Architect and implement major features across the frontend, backend, and database.
Use Codex, Claude, and related tools to accelerate development significantly.
Break large initiatives into coherent, AI-executable implementation plans.
Provide AI agents with the context, constraints, patterns, and acceptance criteria needed to produce reliable code.
Run multiple agents or parallel development workflows where appropriate.
Review and correct all AI-generated code before it reaches production.
Design secure PostgreSQL schemas, authorization rules, APIs, and application flows.
Build with security, privacy, performance, feature gating, testing, observability, and safe rollout in mind.
Lead major refactors while preventing inconsistent patterns and unnecessary technical debt.
Maintain architecture documentation that helps both engineers and AI agents understand the codebase.
Diagnose difficult production issues and improve engineering standards as the platform grows.
Current Technical Direction

The current platform is directionally built around:

React and TypeScript
Vite
Supabase
PostgreSQL
Authentication, storage, and realtime functionality
Automated testing
CI/CD and production deployment workflows

Direct experience with every current technology is not required. However, you must be able to understand an existing codebase quickly, identify architectural risks, and begin shipping high-quality work without requiring extensive supervision.

Required Qualifications
At least eight years of professional software-engineering experience.
Bachelor’s degree in computer science, software engineering, or a closely related field.
Advanced React and TypeScript experience.
Strong PostgreSQL and relational data-modeling expertise.
Experience designing production systems at meaningful scale.
Strong system-design and software-architecture judgment.
Experience providing technical leadership, setting standards, or guiding architectural decisions.
Excellent written and spoken English.
Ability to personally implement substantial production features—not only design or delegate them.
Availability to work entirely within Los Angeles/Pacific Time business hours, which will generally require overnight working hours in the Philippines.
Strong understanding of security, authorization, privacy, testing, performance, and production reliability.
AI-Native Engineering Requirements

We are not looking for someone who occasionally asks ChatGPT to generate a function.

You should be able to demonstrate experience with several of the following:

Using Codex, Claude Code, or comparable agentic development tools on real production systems.
Dividing complex features into effective prompts, tasks, and validation stages.
Supplying agents with architecture documents, coding standards, schemas, and repository context.
Managing large refactors through AI without losing consistency or introducing hidden regressions.
Detecting hallucinated APIs, insecure implementations, incorrect assumptions, and poor architectural decisions.
Coordinating multiple agents or parallel workstreams safely.
Using tests, type checking, code review, and manual validation to verify generated work.
Structuring repositories and documentation so future AI-assisted development becomes faster and more reliable.

The best candidate will view AI as a powerful execution layer while understanding that experienced engineering judgment remains essential.

Strongly Preferred Background

We strongly prefer candidates who have also worked as a:

Business Analyst
Product Manager
Technical Product Manager
Product Owner
Founder or technical co-founder
Senior engineer with substantial product ownership

Formal titles are not mandatory. What matters is your ability to take an incomplete business objective, identify missing requirements, understand the user experience, make sound tradeoffs, and convert it into a technical plan that can be implemented successfully.

Experience with Supabase, row-level security, marketplaces, social platforms, booking systems, payments, automated testing, CI/CD, or feature-flag systems is also valuable.

The Type of Engineer Who Will Succeed

You will likely succeed in this role if you:

Ship quickly without treating security or quality as optional.
Can move from an ambiguous idea to a production-ready implementation.
Make practical architectural decisions rather than overengineering.
Challenge unclear or risky requirements while still maintaining momentum.
Investigate problems independently before escalating them.
Understand where AI can accelerate development and where human review is indispensable.
Communicate tradeoffs clearly to a business-oriented founder.
Take ownership of outcomes rather than only completing assigned tickets.
Prefer building and shipping over spending excessive time in meetings.
Growth and Compensation

The position will begin part-time and can move toward full-time based on performance, product needs, and company growth.

Bellaura is currently unfunded, so the initial compensation is $7–$12 USD per hour. We want to be direct that this is below the long-term compensation expected for someone operating at this level.

For a proven performer, our current intention is to increase compensation significantly after funding, with a target of approximately $20 USD per hour, subject to funding, performance, expanded responsibilities, and a formal compensation agreement. Equity may also become available later for someone who demonstrates exceptional long-term value.

This opportunity is best suited to someone who values early ownership, direct influence over the product, and the ability to establish themselves as a critical technical leader before the company’s next stage of growth.

Selection Process

Qualified candidates may be invited to:

Interview directly with the founder.
Review and discuss a realistic system-design problem.
Demonstrate an AI-assisted development workflow.
Review flawed AI-generated code and identify risks.
Complete a short paid technical exercise.
Provide professional references.
How to Apply

Please submit your resume, LinkedIn profile, GitHub or portfolio links, hourly-rate expectation, availability, and answers to the following three questions. Keep each answer concise and specific.

1. Describe the most substantial production feature or refactor you have completed using Codex, Claude, or another AI development system.

What were you building, how did you structure the work for AI, what context did you provide, and how did you verify the resulting code? Explain what you personally architected, reviewed, corrected, and shipped. Include links, diagrams, screenshots, or a short demonstration when available.

2. How would you architect a feature-gated event-ticketing system with promoter attribution?

Assume users can purchase tickets, promoters receive trackable links, hosts can approve attendees, rejected attendees may require refunds, and access must be protected by user roles.

Briefly describe:

The core PostgreSQL entities and relationships.
Authorization and privacy controls.
How you would prevent duplicate purchases or attribution errors.
The three most important failure cases.
Your testing and rollout strategy.

We are evaluating your reasoning, prioritization, and ability to translate business behavior into a reliable technical design—not the length of your answer.

3. Describe a time you converted an ambiguous business requirement into a successful production system.

What was initially unclear? What questions did you ask? Which technical and product tradeoffs did you make? What did you personally implement, and what measurable result did the finished system produce?