Orbox

AI-First Product (UX/UI) Designer

Ukraine · Remote · Full-Time

Company: Orbox.ai - AI-Native PropTech platform (Orbox aOS)

Location: Ukraine - remote, anywhere in Ukraine (candidate must be located in Ukraine). Office in Lviv opening soon (attendance optional).

Employment: Full-time, long-term

Seniority: Senior / Lead

Reports to: Chief Operating Officer

Works with: The Dubai team - CEO, Concept Design & Engineering team, AI agents. You will be the only product designer on Orbox aOS and own design end to end.

PropTech experience: Not essential; very good if you have direct or indirect experience

English: Advanced (B2+) - daily working language with the Dubai team

Time zone: Dubai is GMT+4, 1-2h ahead of Kyiv - near-full working-day overlap

About

We are building an AI-native SaaS for real estate. The product is a PropTech platform where LLMs and AI agents are not bolted on top - they are the architecture. Owners, operators and guests interact with the AI system through natural language. AI autonomously generates compliance documents, routes staff, answers guest queries from a RAG-indexed knowledge base in real time and orchestrates financial split-payments.

But the product is only half of it.

We are equally an AI-first delivery organization. The way we discover, define and ship is as differentiated as what we ship. Product discovery, specification, design and validation run through a tight loop in which humans operate at the level of intent, structure and judgment, and AI agents do most of the typing. Designs are not throwaway pictures - they feed directly into the machine-readable artifacts our coding and review agents consume.

What you will own & do

AI-First Way of Working

• Daily, deep, native use of AI tools for mockup generation, prototype scaffolding, copy iteration, design exploration, asset generation and design-system upkeep.

• Treat AI tools the way an engineer treats their IDE: opinionated, tuned, integrated into every step of your workflow.

• Co-design, with the Tech Lead and the Business Analyst, the boundary between what you produce by hand and what is generated, transformed or validated by agents.

• Contribute to internal evals from the design side: define what "good" looks like for AI-generated UI and for our user-facing AI experiences.

End-to-End Product Design

• Own the end-to-end product design process: information architecture, user flows, wireframes, high-fidelity mockups and clickable prototypes for web and mobile.

• Translate validated product intent and specifications into clear, usable, beautiful screens and flows - working from the Business Analyst's discovery output, not waiting on hand-holding.

• Keep dense, complex functionality usable: dashboards, multi-tenant views, role-based experiences, real-time data and back-office tooling that people actually enjoy using.

• Own the whole flow, not just the screens: frame the problem with the product team, map the user journey, decide what should exist at all - then design it. You are accountable for the outcome of the experience, not for the delivery of mockups.

• Lead with UX over UI: structure, flows, states, edge cases, copy and decision points come first; visual polish follows and serves them.

• Iterate quickly, kill weak concepts early, and ship surfaces you can stand behind.

Working with the Product Team

• Work closely with the product team daily: discovery, planning and prioritisation with the Chief Operating Officer and the Business Analyst. Design is in the room when scope is decided, not briefed afterwards.

• Challenge requirements from the user's side: propose simpler flows, cut what does not need to exist, and push back when a feature does not earn its place.

• Keep the team aligned remotely: clear async write-ups, recorded walkthroughs and decision logs so a distributed team across Ukraine and Dubai never waits on you to explain a design.

Designing AI & Agent-Driven Interfaces

• Design natural-language and agent-driven interfaces: chat surfaces, mixed conversational + structured UIs, agent hand-offs, transparency of AI actions, edit/undo affordances - core to our product, not decoration.

• Design for the failure modes of LLM-driven products: uncertainty, latency, wrong answers, partial actions - so users stay in control and trust the system.

Design System & Handoff to the AI-First Machine

• Establish and maintain a design system together with engineering: components, tokens, patterns and accessibility baselines - consumable by both humans and code-generation agents.

• Structure design artifacts so they map cleanly onto the spec layer and onto the components our coding agents generate - design that survives translation into code.

• Partner with the Business Analyst so screens, specs and acceptance criteria stay in sync; when the design changes, downstream artifacts change with it.

Validation & Usability

• Run usability sessions on prototypes before engineering writes a line of code; de-risk decisions early.

• Participate in discovery from a design and usability angle - sketch concepts live, pressure-test ideas with real owners, operators and guests.

• Own design QA: measure what shipped versus what was designed, and feed learnings into the next iteration.

What we are looking for

Must have

• 4+ years of relevant experience in product design, UX/UI or product/design hybrid roles, with senior-level ownership of end-to-end design.

• A portfolio showing shipped product surfaces - not just Dribbble shots - including work where you shaped the flow and the product decision, not only the screens.

• 0 → 1 builder: worked directly with Heads and/or Founders and Engineering - not joining an already-scaled product org.

• Hands-on UX/UI ability: high-fidelity mockups, prototypes and design-system work.

• Experience designing for AI/LLM-driven products: chat, agents, mixed conversational + structured UIs, AI-assisted workflows - and you understand their failure modes.

• Comfortable with complex B2B / multi-sided product surfaces: dashboards, multi-tenant SaaS, role-based experiences, real-time data, complex back-office tooling.

• Daily, deep, native use of AI tools: mockup generation, prototyping, copywriting, design exploration. You have a real, opinionated workflow built around them and can defend your choices.

• Design-system craft: components, tokens, patterns and accessibility - structured cleanly enough that engineers (and agents) do not have to guess.

• Comfortable working directly with engineering on feasibility and component handoff.

• Experience-first mindset: you talk about users, jobs and outcomes before pixels.

• Strong written and verbal English (B2+); remote-ready in a distributed team (Ukraine + Dubai) with async-friendly communication.

Strong advantage (Nice to have)

• Background in PropTech, hospitality tech, Fintech or multi-sided marketplace platforms.

• Exposure to IoT / smart-home product surfaces, payment flows or compliance/regulatory workflows.

• Experience setting up or significantly improving an AI-assisted design workflow (exploration → mockups → prototype → validation) on a real product.

• Motion / interaction design and prototyping depth for conversational and agentic UIs.

Why this role

You will help build the first AI-native operating system for real estate in Dubai and the AI-first design practice that shapes it. Both are differentiators, both are hard and both are yours to own at the senior level.

• Genuine design ownership - of the product's UX, its design system and the agent-driven interfaces. This is not a "pixel-push the tickets" role.

• Clear growth trajectory - this role evolves into Lead Product Designer and then Head of Design as the team scales.

• Direct access to the CEO and the Chief Operating Officer - short decision loops, no middle management.

• Technically ambitious product surface - AI agents, RAG, IoT, real-time systems, government and regulatory APIs and eventually tokenization infrastructure.

• AI-first by default - you will co-design how a product gets designed and validated inside an AI-first delivery machine.

• Seat at the product table - you shape what gets built, not just how it looks once decided.

• Remote-first across Ukraine, Lviv office opening soon (attendance optional), Dubai HQ (One Central Plaza) as the company base.

Conditions

• Full-time, long-term; contract format agreed individually.

• Remote, anywhere in Ukraine (must be located in Ukraine).

• Please include a link to your portfolio.

AI-First Product Analyst

Ukraine · Remote · Full-Time

Company: Orbox.ai - AI-Native PropTech Operating System for Real Estate (Orbox aOS)

Location: Ukraine - remote, anywhere in Ukraine (candidate must be located in Ukraine). Office in Lviv opening soon (attendance optional).

Employment: Full-time, long-term

Seniority: Senior

Reports to: Chief Operating Officer

Works with: The Dubai team - CEO, Product Designer, Concept Design & Engineering team, AI agents

PropTech experience: Not essential; very good if you have direct or indirect experience

English: Advanced (B2+) - daily working language with the Dubai team

Time zone: Dubai is GMT+4, 1-2h ahead of Kyiv - near-full working-day overlap

About

We are building an AI-native operating system for real estate. The product is a PropTech platform where LLMs and AI agents are not bolted on top - they are the architecture. Owners, operators and guests interact with the AI system through natural language. AI autonomously generates compliance documents, routes staff, answers guest queries from a RAG-indexed knowledge base in real time and orchestrates financial split-payments.

But the product is only half of it.

We are equally an AI-first delivery organization. The way we discover, define and ship is as differentiated as what we ship. Product discovery, specification, design and validation run through a tight loop in which humans operate at the level of intent, structure and judgment, and AI agents do most of the typing. Specs are not documents we forget about - they are machine-readable artifacts our coding and review agents consume directly.

What you will own & do

AI-First Way of Working

• Daily, deep, native use of AI tools for agent-assisted research synthesis, competitor teardowns, spec drafting, documentation upkeep and metric analysis.

• Treat AI tools the way an engineer treats their IDE: opinionated, tuned, integrated into every step of your workflow.

• Co-design the boundary between what you produce by hand and what is generated, transformed or validated by agents.

Product Discovery

• Run end-to-end market research and discovery to uncover what to build: turn raw intent, customer interviews, market signal and competitor analysis into clearly framed product opportunities, validated against real owner, operator and guest needs.

• Define and own the product opportunity backlog: hypotheses, problem statements, success metrics and the criteria for which problems we solve next versus park.

• Rapid concept validation: dry tests, prototype-based interviews and lightweight A/B tests - before engineering capacity is committed.

• Evidence over opinion: maintain a living research repository so any decision can be traced back to the user signal that justified it.

Product Documentation for the AI-First Delivery Machine

• Own the doc & spec layer: write validated product documentation and convert it into clear, structured, machine-readable specifications that our orchestrator and coding agents can implement, test and evolve reliably.

• Write product documentation that is unambiguous, testable and versioned - the source of truth for engineering, QA, evals and onboarding.

• Keep specifications in sync with reality: when the product changes, the spec changes first; when the spec changes, downstream agents pick it up.

• Partner with the Product Designer so specs, screens and acceptance criteria stay aligned end to end.

• Produce initial clickable PoCs to test the PRD before handing over to design.

Working with the Dubai Team

• Plug into the existing team from day one: daily discovery, planning and prioritisation with the Chief Operating Officer, the Designer and engineering in Dubai - you are part of the core team, not an outsourced resource.

• Run product work remotely without friction: clear async write-ups, recorded walkthroughs, decision logs and specs that stand on their own.

• Keep the Dubai context alive: owners, operators, regulators and market specifics are in Dubai; you bring that into every spec through research, interviews and close work with the on-site team.

Validation, Metrics & Product Quality

• Define product success metrics, leading indicators and guardrails for every shipped capability; instrument them with engineering.

• Co-own the loop between what we shipped and what users actually did with it; feed learnings back into discovery.

• Partner with engineering on UAT and AI-output evaluation - treat LLM outputs as something to be measured, not trusted.

What we are looking for

Must have

• 4+ years of relevant experience as a product analyst, business analyst or product lead, with ownership of market research, ideation, discovery and spec writing.

• 0 → 1 builder: worked directly with Heads and/or Founders and Engineering - not joining an already-scaled product org.

• Daily, deep, native use of AI tools: research synthesis, spec drafting, documentation, analysis. You have a real, opinionated workflow built around them and can defend your choices.

• Excellent product documentation skills: user stories, acceptance criteria, edge cases, data contracts, state behaviour - clear, testable, unambiguous, and structured enough that engineers (and agents) do not have to guess.

• Strong product discovery skills: you can run interviews, synthesize signals, prioritize hypotheses and design experiments that actually de-risk decisions.

• Rigorous, evidence-driven mindset: treat opinions as hypotheses, define success up front, instrument outcomes, kill what is not working.

• Comfortable with complex B2B / multi-sided product surfaces: dashboards, multi-tenant SaaS, role-based experiences, real-time data, complex back-office tooling.

• Strong written and verbal communication in English (B2+), running discovery and documentation under startup timelines while keeping quality and traceability intact.

• Remote-ready: comfortable in a distributed product team (Ukraine + Dubai), with async-friendly communication and the self-direction to own outcomes without a manager in the room.

Strong advantage (Nice to have)

• Experience defining specs or workflows for AI agents, RAG systems, prompt-driven features or agent orchestration.

• Background in PropTech, hospitality tech, Fintech or multi-sided marketplace platforms.

• Exposure to IoT / smart-home product surfaces, payment flows, compliance or regulatory workflows.

• Experience setting up or significantly improving an AI-assisted product workflow (research → spec → validation) on a real product.

• Fluency with analytics / instrumentation tooling and comfort reading data to back decisions.

Why this role

You will help build the first AI-native operating system for real estate in Dubai and the AI-first product practice that shapes it. Both are differentiators, both are hard and both are yours to own at the senior level.

• Genuine product co-ownership - of discovery and of the spec layer that feeds our AI delivery machine. This is not a "gather requirements and write tickets" role.

• Clear growth trajectory - this role evolves into AI-First Product Manager and then Head of Product as the team scales.

• Direct access to founders and the Chief Operating Officer - short decision loops, no middle management.

• Technically ambitious product surface - AI agents, RAG, IoT, real-time systems, government and regulatory APIs and eventually tokenization infrastructure.

• AI-first by default - you will co-design how a product gets discovered, specified and validated inside an AI-first delivery machine.

• Remote-first across Ukraine, Lviv office opening soon (attendance optional), Dubai HQ (One Central Plaza) as the company base.

Conditions

• Full-time, long-term; contract format agreed individually.

• Remote, anywhere in Ukraine (must be located in Ukraine).

AI-First Senior Software Engineer

Ukraine · Remote · Full-Time

Company: Orbox.ai - AI-Native PropTech Operating System for Real Estate

Location: Ukraine - remote, anywhere in Ukraine (candidate must be located in Ukraine)

Employment: Full-time, permanent

Seniority: Senior

Reports to: Tech Lead

Works with: AI-Engineer, Product Analyst, UI/UX Designer, QA Engineer

PropTech experience: Not essential, very good if has direct or indirect experience

English: Advanced (B2-C1)

About

We are building an AI-native operating system for real estate. The product is a PropTech platform where LLMs and AI agents are not bolted on top - they are the architecture. Owners, operators and guests interact with the AI system through natural language. AI autonomously generates compliance documents, routes staff, answers guest queries from a RAG-indexed knowledge base in real time and orchestrates financial split-payments.

But the product is only half of it.

We are equally an AI-first delivery organization. The way we discover, define and ship is as differentiated as what we ship. Specs, stories and designs are machine-readable artifacts our coding and review agents consume directly - and senior engineers are the ones who design the system, direct the agents and own every line that reaches production.

The role

This is the role that turns machine-readable specs into production software - by leading AI agents, not by typing every line yourself.

You will report directly to the Chief Operating Officer, with short decision loops to founders and direct access to product, design and QA.

This is a hands-on senior engineering role at the core of the delivery machine. Most of our code is written by AI coding agents against machine-readable specs. That makes senior engineering judgment more valuable, not less: agents write fast, but still pick wrong abstractions, miss edge cases, leak data across tenants and ship code that passes its own tests and breaks in production. You are the engineer who designs the system, sets the guardrails and owns what gets merged.

You will build and ship features end to end across backend, frontend and integrations: service design, data models, APIs, UI, government and third-party integrations, AI features (LLM agents, RAG, document generation) and the infrastructure they run on.

You will work side by side with the AI-First Product Analyst (who writes the specs), Product Designers (who own the mockups) and QA (who holds the release bar). You will use our shared Claude Team / Claude Code with premium seating along with the company's AI tools daily, deeply and natively - not as a novelty, but as the default way you work.

We operate in a fast-moving startup environment where speed and precision both matter. You must be opinionated about which engineering tasks AI does well today (boilerplate, refactors, tests, migrations, docs), which it does not (architecture, security boundaries, trade-off calls, debugging subtle production issues) - and how to combine both deliberately.

What you will own & do

AI-First Engineering

• Daily, deep, native use of AI coding agents for implementation from specs, refactoring, test writing, code review, debugging and documentation.

• Treat agents like a team you lead: clear specs in, reviewed code out - you own the context, rules files, guardrails and the review bar.

• Build and improve our agentic delivery pipeline: repo conventions, agent instructions, MCP tooling and CI checks that keep agent output safe to merge.

• Contribute to internal evals from the engineering side: define what “good” looks like for AI-generated code and for our user-facing AI features.

Product Engineering

• Own features end to end: from spec & acceptance criteria to design, implementation, tests, deployment and monitoring on prod.

• Design clean service boundaries, data models and APIs for a multi-tenant B2B2C platform with role-based access.

• Build complex frontend surfaces: dashboards, real-time data, multi-step workflows, back-office tooling.

• Integrate with government and regulatory APIs, payment providers and third-party systems - reliably, idempotently, with proper error handling and audit trails.

AI & LLM Systems

• Build production AI features: LLM agents, tool calling, RAG pipelines, compliance document generation - with grounding, fallbacks and cost control.

• Engineer the non-deterministic layer: prompt versioning, structured outputs, guardrails against hallucinations and prompt injection, tenant-safe retrieval.

• Instrument AI behaviour with tracing, logging and metrics - treat AI output as something to be measured, not trusted.

Engineering Quality & Ownership

• Own the merge bar: review agent and human PRs, enforce architecture, security and performance standards.

• Write automated tests and CI that make agent output safe to ship; partner with QA on test strategy and release readiness.

• Feed spec & story defects back upstream: when the work item is wrong or ambiguous, it gets fixed at the spec layer, not hacked around in code.

• Shape the engineering practice at an early stage: conventions, environments, observability, incident handling - lightweight enough for startup speed, rigorous enough to trust.

What we are looking for

Must have

• 4+ years of hands-on software engineering on production web products, with senior-level ownership of a system or major product area.

• Strong full-stack skills: modern backend (TypeScript / Node.js or Python), modern frontend (React / Next.js or similar) and relational databases (PostgreSQL or similar).

• Daily, deep, native use of AI coding tools (Claude Code, Cursor or similar) in your engineering workflow. You have a real, opinionated workflow built around them and can defend your choices.

• Hands-on experience building LLM-based features: agents, tool calling, RAG, structured outputs - shipped to production, not just demos.

• Solid system design: multi-tenant SaaS, role-based access, API design, async processing, third-party integrations.

• Critical code review skills: you read AI-generated code with suspicion and catch what agents miss - security holes, data leaks, wrong abstractions, hidden complexity.

• Cloud & DevOps fluency: Docker, CI/CD, at least one major cloud (AWS / GCP / Azure), logging and monitoring.

• 0 → 1 mindset: comfortable in an early-stage team, working directly with founders and product, shipping fast without losing rigor.

• Strong written and verbal communication in English - including specs, PR descriptions and technical discussions.

Strong advantage (Nice to have)

• Background in PropTech, hospitality tech, Fintech or multi-sided marketplace platforms.

• Exposure to payment flows, compliance / regulatory workflows, document-generation systems or government API integrations.

 Experience with LLM evals and observability (Langfuse, LangSmith or similar) and vector databases.

• Real-time systems, IoT or tokenization / blockchain infrastructure.

Why this role

You will help build the first AI-native operating system for real estate in Dubai and define how software gets built when AI agents write most of the code.

• Genuine engineering ownership.

• Clear growth trajectory - Tech Lead / Engineering Lead.

• Direct access to founders and the Chief Operating Officer.

• Technically ambitious product surface - AI-native, Agentic system, RAG, IoT, real-time systems, government APIs, tokenization.

• AI-first by default.

AI-First Senior QA Engineer (Manual)

Ukraine · Remote · Full-Time

Company: Orbox.ai - AI-Native PropTech Operating System for Real Estate

Location: Ukraine - remote, anywhere in Ukraine (candidate must be located in Ukraine)

Employment: Full-time, permanent

Seniority: Senior

Reports to: Technical Lead 

Works with: Product Analyst, Product Designer, Engineering team, Fleet of Agents

PropTech experience: Not essential; very good if you have direct or indirect experience

English: Advanced (B2+)

About

We are building an AI-native operating system for real estate. The product is a PropTech platform where LLMs and AI agents are not bolted on top - they are the architecture. Owners, operators and guests interact with the AI system through natural language. AI autonomously generates compliance documents, routes staff, answers guest queries from a RAG-indexed knowledge base in real time and orchestrates financial split-payments.

But the product is only half of it.

We are equally an AI-first delivery organization. The way we discover, define and ship is as differentiated as what we ship. Specs, stories and designs are machine-readable artifacts our coding and review agents consume directly — and quality is verified by a human who knows exactly where agents fail, where specs lie and where the product breaks in real hands.

The role

This is the role that decides whether what we ship actually works  for humans and for the agents that built it.

You will report directly to the Chief Operating Officer, with short decision loops to founders and direct access to engineering.

This is a hands-on, manual-first QA role at the core of the delivery machine. Most of our code is written by AI agents against machine-readable specs. That makes human quality judgment more valuable, not less: agents pass their own checks and still ship broken flows, wrong edge-case behaviour and UX that technically matches the spec but fails the user. You are the last honest reader of the product before it reaches staging review and then customers on prod.

You will own manual testing end to end: exploratory testing, spec-based test design, UAT coordination, regression passes and release sign-off. You will test not just deterministic UI flows, but AI-driven behaviour  agent responses, RAG answers, document generation  where “expected result” is a judgment call, not an assert.

You will work side by side with the AI-First Product Analyst (who writes the specs you test against) and engineering (whose agents implement them). You will use our shared Claude Team / Cowork with premium seating along with the company's AI tools daily, deeply and natively — not as a novelty, but as the default way you work.

We operate in a fast-moving startup environment where speed and precision both matter. You must be opinionated about which QA tasks AI does well today (test-case generation, coverage analysis, log triage), which it does not (exploratory judgment, UX intuition, risk feel) — and how to combine both deliberately.

What you will own & do

AI-First Way of Working

• Daily, deep, native use of AI tools for test-case generation from specs, coverage gap analysis, bug report drafting, log and session triage, regression checklist upkeep.

• Treat AI tools the way an engineer treats their IDE: opinionated, tuned, integrated into every step of your workflow.

• Contribute to internal evals from the QA side: define what “good” looks like for AI-generated code, AI-generated test artifacts and our user-facing AI features.

Manual Testing & Test Design

• Own manual testing end to end: exploratory sessions, spec & story-based test design, edge cases, negative paths, cross-role and multi-tenant scenarios.

• Convert machine-readable specs & stories with acceptance criteria into structured, traceable test cases and checklists — every requirement maps to a verification.

• Run deep exploratory testing where scripted coverage ends: real-world flows, messy data, weird devices, impatient users.

• Verify complex B2B2C surfaces: dashboards, role-based access, real-time data, payment flows, document generation, back-office tooling.

Testing AI-Driven Behaviour

• Test the non-deterministic layer: agent conversations, autonomously generated compliance documents — correctness, groundedness, tone, failure modes.

• Design and run structured evaluation of LLM outputs with the Analyst and engineering: treat AI output as something to be measured, not trusted.

• Hunt for hallucinations, prompt-injection surfaces, permission leaks across tenants and roles, and silent agent failures.

Quality Process & Release Ownership

• Own release readiness: regression scope, smoke passes, UAT coordination with stakeholders, GO/NO-GO input for every release.

• Write bug reports engineers (and agents) can act on without a follow-up question: environment, steps, expected vs actual, evidence, severity.

• Feed spec & story defects back upstream: when the work item is wrong or ambiguous, it gets fixed at the spec/story layer, not patched in QA.

• Build the QA practice from scratch: process, tooling, test data, defect workflow in Jira — lightweight enough for startup speed, rigorous enough to trust.

What we are looking for

Must have

 4+ years of hands-on manual QA experience on web products, with senior-level ownership of quality for a product or major product area.

• 0 → 1 builder: comfortable being the first and only QA, setting up the practice yourself, working directly with founders and engineering — not joining an already-scaled QA org.

• Experience testing LLM-based features, chatbots, RAG systems or agent workflows — including designing evals or output rubrics.

• Daily, deep, native use of AI tools in your QA workflow: test generation, triage, analysis, documentation. You have a real, opinionated workflow built around them and can defend your choices.

• Excellent test design craft: from acceptance criteria to test cases, edge cases, negative scenarios and risk-based prioritization — structured, traceable, unambiguous.

• Strong exploratory testing instincts: you find the bugs no script would — and can explain how you found them.

• Sharp written bug reporting and strong verbal communication in English (C1+), under startup timelines, without losing rigor.

• Comfortable with complex B2B / multi-sided product surfaces: multi-tenant SaaS, role-based access, real-time data, payments, back-office tooling.

 Working knowledge of APIs and databases for verification: reading API responses (Postman or similar), basic SQL to check data behind the UI, reading logs.

Strong advantage (Nice to have)

• Background in PropTech, hospitality tech, Fintech or multi-sided marketplace platforms.

• Exposure to payment flows, compliance / regulatory workflows or document-generation systems.

• Test automation literacy (Playwright, Cypress or similar) — enough to direct agents that write automation, even if you don't write it daily.

Why this role

You will help build the first AI-native operating system for real estate in Dubai and define what quality means when AI agents write most of the code. Both are differentiators, both are hard and both are yours to own at the senior level.

• Genuine quality ownership — you build the QA practice from zero and hold the release bar. This is not a “execute someone else's test cases” role.

• Clear growth trajectory — this role evolves into AI-First QA Lead / Head of Quality as the team scales.

• Direct access to founders and the Chief Operating Officer — short decision loops, no middle management.

• Technically ambitious product surface  AI-native, Agentic system, RAG, IoT, real-time systems, government and regulatory APIs and eventually tokenization infrastructure.

 AI-first by default — you will co-design how quality assurance works inside an AI-first delivery machine.