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.
• 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.
