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 design patterns Experience with computer vision, image recognition, or retail execution platforms strongly preferred Prior exposure to FMCG, CPG, or retail technology platforms is a significant advantage Technical Skills Cloud: Azure (primary), AWS/GCP (secondary) — infrastructure design, cost optimisation Mobile: iOS (Swift/Objective-C), Android (Kotlin/Java), cross-platform considerations (React Native, Flutter) ML/AI: Model serving pipelines, MLOps practices, CV model deployment (object detection, classification) Integration: REST APIs, event-driven architectures (Kafka, Service Bus) Data: Cosmos DB, PostgreSQL, Data bricks, cloud storage lifecycle management, data governance frameworks DevOps: Kubernetes, Docker, CI/CD pipelines, infrastructure monitoring and alerting Soft Skills & Behaviours Exceptional ability to translate complex technical architecture into clear, business-relevant narratives for executive audiences Strong cross-functional collaborator — equally effective with product managers, data scientists, field operations leads, and compliance teams Demonstrated ownership mindset — proactively identifies risks, escalates with solutions, and drives resolution end-to-end Comfortable operating in ambiguous, multi-market environments with competing priorities Excellent written communication — capable of producing publication-quality TRDs, PRDs, and architecture decision records