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 ST 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 d…