Senior Full Stack Engineer (Part-Time, Unpaid)

UNPAID SENIOR FULL STACK ENGINEER — PART-TIME, REMOTE

Properta AI Technologies Ltd | Applicants based in Dubai or India

COMPENSATION (PLEASE READ FIRST)

This is a part-time, unpaid pre-launch opportunity. Properta cannot offer a salary or stipend now. We are looking for an experienced engineer who can contribute reliable hours alongside existing commitments.

If Properta launches successfully and generates sufficient revenue or secures investment, we hope to explore a paid, full-time role with the right person. A future role, salary and start date are not guaranteed.

Before work begins, we will agree in writing on weekly availability, initial deliverables and a review date. We value realistic commitments, visible progress and early communication if availability changes.

ABOUT PROPERTA

Properta is building an independent property intelligence platform. Our first product turns property data into clear, evidence-based reports that help people assess residential properties in Dubai.

Each report should explain the supported price range, the comparable evidence behind it, the strength and limitations of that evidence, and when there is insufficient evidence to support a conclusion. Rental and return information is included only where the underlying evidence and cost assumptions support it.

We have an existing customer-facing experience, analytical components and substantial data assets. Our immediate engineering goal is to integrate and strengthen them into a secure, reliable production platform.

REPORTING STRUCTURE

You will report directly to Properta’s CTO, who will guide engineering priorities, review technical work and coordinate delivery. The CTO reports directly to Properta’s founder. You will work with the CTO and product team on agreed MVP deliverables.

THE ROLE

This is a hands-on, end-to-end engineering role. We need someone who can personally take an agreed capability from requirements and architecture through implementation, testing, Azure deployment and production support. The role spans the customer application, Python services and APIs, property-data processing, analytical outputs, practical AI integration, security and cloud operations.

You will implement the agreed platform architecture at component level, make sound engineering decisions within its boundaries and raise unresolved architecture choices early. The initial scope will be selected to fit your strengths and agreed part-time hours; you will not be expected to deliver every area below at once.

WHAT YOU WILL WORK ON

• Customer application: Build and refine production-ready React and TypeScript journeys for property entry, confirmation, onboarding, accounts, report requests, report viewing and sharing. Connect the customer experience to secure backend services, with authorization, entitlements and report state controlled server-side.

• Backend and APIs: Develop Python services and secure REST APIs for authentication, authorization, report generation, entitlements, subscriptions, payments, administrative operations and PDF delivery. Implement clear API contracts, API versioning, error handling, idempotency, correlation IDs and traceability across requests and jobs. Integrate third-party services and secure webhooks where needed.

• Data and analytical engineering: Integrate authorised property-data pipelines and analytical components with production services using Python, SQL, PostgreSQL and, where appropriate, DuckDB. Build or improve processing, ETL/ELT, validation and data-quality controls. Handle missing, inconsistent, duplicate and suspicious records while preserving provenance, lineage and reproducibility.

• Evidence-controlled reports: Implement workflows for comparable selection, exclusions, confidence rules and clear handling of insufficient evidence. Keep ready and off-plan evidence separate, and preserve traceability from source data to customer-facing conclusions.

• AI engineering: Integrate LLM capabilities into production workflows where they add value. Work with model APIs, structured outputs, prompt management, evaluation, guardrails, observability and cost controls. Apply RAG, embeddings or agent workflows where the product requires them. This is practical AI application engineering; advanced model research is not required.

• Reliable processing: Design asynchronous jobs, bounded retries, idempotency and failure handling so timeouts or dependency failures do not create duplicate reports, duplicate payments or incorrect use of a customer’s report allowance.

• Secure report access: Ensure customers can reopen reports, download authorised PDFs and share reports through controlled links that can expire or be revoked.

• Azure and production engineering: Build and operate services on Microsoft Azure with appropriate development, staging and production separation. Implement secrets management, least-privilege access, CI/CD, backups and recovery procedures. Establish observability through structured logging, metrics, health checks, alerts, correlation IDs and distributed tracing where appropriate.

• Testing and support: Write meaningful automated tests, investigate production failures, identify root causes and deliver durable fixes. Build services that are secure, observable and independently testable.

REQUIRED EXPERIENCE

• Hands-on production ownership: You have personally built, shipped and supported substantial features in a live product and can explain exactly what you implemented. Experience taking a prototype or existing codebase into production is particularly relevant.

• Frontend: Strong React, TypeScript and modern web application experience.

• Backend: Strong Python and REST API engineering experience, or substantial backend experience with a clear willingness to work extensively in Python.

• Data: Strong SQL and relational database experience, with practical data processing, validation or analytical integration experience.

• Cloud and delivery: Hands-on experience deploying and operating production applications on Microsoft Azure, plus Docker, Git and CI/CD.

• AI integration: Practical experience integrating LLM or other AI capabilities into applications, or demonstrated ability to implement and evaluate such integrations in production.

• Security and quality: Experience with role-based access control (RBAC), authorization, API security, OAuth/OIDC, rate limiting, encryption in transit and at rest, secrets management, automated testing, monitoring and production incident resolution.

• Architecture and execution: Ability to implement an agreed architecture across application, cloud and data layers, raise unclear decisions early, and deliver tested work within consistent part-time hours.

We are primarily seeking 8+ years of professional engineering experience, or equivalent evidence of strong hands-on production ownership.

Experience with PostgreSQL, Azure Container Apps, Azure Key Vault, DuckDB, payments and subscriptions, asynchronous processing, RAG and property or financial data platforms is valuable. Real estate experience is useful but not required.

EDUCATION AND LANGUAGE

A Bachelor’s or Master’s degree in Computer Science, Engineering or a related field is preferred. Equivalent strong production engineering experience will be considered.

Professional working English is required for engineering discussions, documentation and collaboration. Arabic is a plus, not a requirement.

LOCATION AND AVAILABILITY

The role is fully remote. Applicants must be based in Dubai or India and available for regular overlap with Dubai business hours.

Please be candid about the number of hours you can reliably contribute each week. This opportunity is intended for someone who understands the unpaid terms before joining and can complete an agreed initial milestone alongside other commitments.