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Senior Software Engineer – AI, Python & Rust

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Summary

Owns design, development, deployment and improvement of secure, scalable software and AI/LLM-enabled business apps using Python and Rust, including mobile backends, REST APIs and ERP/CRM integrations. Works hands-on with the CDO in a startup-style environment covering the full SDLC and AI lifecycle.

Senior Software Engineer - AI, Python & Rust

6-8

Ideacrate

Full-Time

AED 6000 - 7000 (Monthly)

Role Purpose:

Own the design, development, integration, deployment and continuous improvement of secure, scalable software and AI-enabled business applications. Work closely with the CDO to translate business requirements into reliable products and digital solutions, with a hands-on, startup-oriented approach.

Key responsibilities

Software engineering & architecture

  • Develop and maintain production software using Python and Rust, selecting each language where technically appropriate.
  • Design backend services, APIs, databases and scalable application architecture; own code reviews, testing, security and performance.
  • Manage the software development lifecycle from requirements and design through CI/CD, deployment, monitoring and maintenance.
  • Build and integrate AI-enabled features, LLM applications, intelligent workflows and automation.
  • Own the AI lifecycle: use-case definition, data preparation, model/API selection, evaluation, deployment, monitoring and improvement.
  • Implement data protection, access controls, testing and human oversight for AI solutions.

Mobile applications & integrations

  • Build backend services supporting iOS/Android applications, including authentication, notifications and payment or third-party integrations as required.
  • Develop REST APIs, webhooks and middleware connecting ERP, CRM, HRMS and other business platforms.
  • Ensure secure data synchronization, resilient error handling, observability and integration documentation.
  • Translate business needs into technical specifications, delivery milestones and MVPs; prioritize speed with maintainability.
  • Coordinate with the CDO, internal stakeholders and vendors; communicate risks, progress and trade-offs clearly.
  • Produce architecture diagrams, API documentation, release notes, runbooks and handover materials.

Required qualifications & experience

  • 6-8 years of professional software engineering experience, including hands-on product development.
  • Strong production Python skills and practical Rust development experience.
  • Demonstrable delivery of AI applications across development, evaluation, deployment and monitoring.
  • Experience with mobile application backends, APIs, ERP/CRM integrations and relational databases.
  • Experience in a startup, scale-up or product-owning organization; direct product ownership preferred over exclusively outsourced service delivery.
  • Working knowledge of cloud infrastructure, Git, CI/CD, containers, testing and secure engineering practices.
  • Excellent spoken and written English, stakeholder communication and technical documentation.
  • Bachelor’s degree in Computer Science, Software Engineering or related discipline, or equivalent demonstrated experience.

Preferred exposure

AWS/Azure/GCP; PostgreSQL/MySQL; Docker/Kubernetes; RAG, LLM evaluation and MLOps; Flutter/React Native ecosystems; Odoo, Microsoft Dynamics or Salesforce; retail, education, entertainment or other consumer-facing products.

Performance scorecard (proposed KPIs)

Targets below are proposed for CDO approval after a 30-day baseline and should be calibrated to project complexity, available resources and agreed delivery scope.

KPI Weight Proposed measure / target Review

Delivery predictability 20% ≥90% of committed sprint/milestone deliverables completed on time; changes documented and approved Monthly

Quality & production stability 20% No unresolved critical defects at release; ≥95% of agreed automated tests pass; severity-1 incidents reviewed with corrective actions Monthly

AI solution delivery & effectiveness 20% Deliver agreed AI use cases against acceptance criteria; document evaluation, accuracy/quality, cost and monitoring before release Quarterly

Integration reliability 15% ≥99% successful scheduled integration transactions (excluding third-party outages); failures monitored and reconciled Monthly

Engineering standards & security 10% 100% of production changes peer-reviewed or CDO-approved; no overdue critical security findings within agreed remediation SLA Monthly

Documentation & handover 10% 100% of production services have current API/architecture notes, deployment instructions and operational runbooks Quarterly

Stakeholder collaboration 5% Weekly progress/risk reporting; ≥4/5 average stakeholder feedback on communication and responsiveness Quarterly

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