AI Product Architect

Overview We are looking for a Product Architect for our Image recognition solution, responsible for the end-to-end technical architecture of the product. You will bridge product strategy and engineering execution, defining how the product scales across markets, integrates with enterprise systems, and evolves with AI/CV innovation. This role works in close partnership with the Global Lead, mobile/SDK engineering team, Backend engineering, data science teams, and S&T leadership. You will own architecture decisions across mobile, backend, cloud infrastructure, ML inference, and data pipelines — ensuring the platform meets global security, compliance, and performance standards while remaining agile enough to support continuous market deployments.

Responsibilities Platform Architecture & Design

• Define and maintain the end-to-end technical architecture for the IR product across mobile, API, ML pipeline, and cloud layers
• Design scalable, multi-region cloud infrastructure on Azure (API Management, Blob Storage, Azure Functions, Cosmos DB, KubeRay/Ray Serve)
• Lead architecture decisions for mobile app features, edge/cloud validation modes, and offline-first mobile scenarios
• Ensure architecture supports high-volume concurrent field usage for global markets
• Define data contracts, API schemas, and integration patterns between mobile app, SDK, backend services, and Salesforce apps

AI/CV Integration & Innovation

• Architect the ML inference pipeline for computer vision models including SKU detection, planogram compliance, and share-of-shelf measurement
• Design model deployment and versioning strategies using KubeRay/Ray Serve or equivalent orchestration platforms
• Collaborate with data science teams to establish model accuracy baselines, A/B testing frameworks, and continuous learning pipelines
• Evaluate and integrate emerging AI capabilities — including LLMs, VLMs, and agentic AI — into the IR Product platform roadmap

Mobile & Integration Architecture

• Define iOS and Android architecture standards for geo-fencing, image capture, local caching, and sync behaviour
• Establish mobile contractor technical standards, code review frameworks, and platform-specific constraints documentation
• Design Salesforce integration patterns for field rep workflows, task assignments, and audit result reporting
• Architect authentication, session management, and device-level security controls for global field deployments

Infrastructure, Reliability & Security

• Own infrastructure architecture for reliability, fault tolerance, and disaster recovery — including GCS fault tolerance and Redis integration for KubeRay head pod stability
• Define storage architecture and lifecycle policies to address accumulation issues (zip files, image blobs, log data) at scale
• Conduct root cause analysis (RCA) for critical infrastructure incidents and produce executive-grade escalation documentation
• Ensure infrastructure architecture meets GDPR, India DPDP Act, and market-specific data privacy regulations for GPS and biometric data

Data Governance & Compliance Architecture

• Design privacy-by-design data flows for GPS location data, field rep identifiers, and store imagery in compliance with GDPR, DPDP, and other applicable frameworks
• Define data residency, data minimisation, and retention policies across global cloud deployments
• Establish security architecture standards for mobile app communications, API authentication, and cloud storage access controls

Stakeholder Engagement & Documentation

• Produce clear, executive-facing architecture documentation, TRDs (Technical Requirements Documents) in partnership with the Global PM
• Present architecture proposals and trade-off analyses to leadership and cross-functional stakeholders
• Mentor Engineering team on product architecture standards and best practices
• Maintain a living architecture registry — covering system diagrams, ADRs (Architecture Decision Records), and integration maps

Qualifications Experience

• 12-15+ years in software/product architecture roles, with at least 3 years in mobile-first or AI/ML-integrated platforms
• Proven experience architecting cloud-native platforms on Azure (API Management, Functions, Blob Storage, Cosmos DB)
• Hands-on experience with ML inference infrastructure — KubeRay, Ray Serve, TorchServe, or equivalent
• Strong background in mobile architecture for iOS and/or Android, including offline-first desi…