Senior Software Engineer AI Python And Rust

Job Description:

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.

AI development lifecycle

• 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.

Product ownership & collaboration

• 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.

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.

KPIWeightProposed measure / targetReview

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

Quality & production stability20%No unresolved critical defects at release; ≥95% of agreed automated tests pass; severity‑1 incidents reviewed with corrective actionsMonthly

AI solution delivery & effectiveness20%Deliver agreed AI use cases against acceptance criteria; document evaluation, accuracy/quality, cost and monitoring before releaseQuarterly

Integration reliability15%≥99% successful scheduled integration transactions (excluding third‑party outages); failures monitored and reconciledMonthly

Engineering standards & security10%100% of production changes peer‑reviewed or CDO‑approved; no overdue critical security findings within agreed remediation SLA Monthly

Documentation & handover10%100% of production services have current API/architecture notes, deployment instructions and operational runbooksQuarterly

Stakeholder collaboration5%Weekly progress/risk reporting; ≥4/5 average stakeholder feedback on communication and responsivenessQuarterly