Solutions Architect
Role Overview
Own the end-to-end technical design of a large AI video analytics platform spanning edge inference, video ingestion, model serving, event distribution, data platforms, and enterprise integration.
The platform serves multiple business domains across thousands of operational sites, with most inference at the edge and central workloads on Azure.
Key Skills for This Role
Full Job Posting
Role overview
Own the end-to-end technical design of a large AI video analytics platform spanning edge inference, video ingestion, model serving, event distribution, data platforms, and enterprise integration.
The platform serves multiple business domains across thousands of operational sites, with most inference at the edge and central workloads on Azure.
Architecture and infrastructure
- Set target-state, multi-tenant, deployment, workload-tiering, and edge/cloud architecture; define availability, latency, recovery, and failover baselines.
- Own edge hardware, GPU sizing, fleet orchestration, device health, remote recovery, model porting, inference performance, and capacity planning.
- Design computer vision and model lifecycle systems, including training, evaluation, rollout, drift detection, accuracy criteria, and responsible AI review.
Integration, data, and operations
- Own VMS, enterprise, data, and domain-specific integrations; define canonical schemas and reliable event patterns; automate site and camera onboarding.
- Own data platform, retention, archival, governance, privacy, observability, SLOs, runbooks, release safety, and FinOps.
- Lead architecture governance, mentoring, dependency management, presales feasibility, and operational handover.
Required qualifications
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, and 12+ years in software and platform engineering.
- Substantial Solution or Enterprise Architect experience and first-hand architecture of large-scale distributed video or streaming systems.
- Required expertise includes distributed systems, hands-on Azure, computer vision and deep learning, production inference, edge AI, video engineering, enterprise VMS, Kubernetes, infrastructure as code, GitOps, observability, data platforms, and security and privacy architecture.
- Strong communication skills and ability to engage with executives, engineers, delivery teams, and enterprise stakeholders.
Preferred qualifications
- Retail technology, telecommunications infrastructure, or oil, gas, and process industry domain experience.
- OT/ICS exposure, responsible AI governance, prior delivery in India or APAC, or experience with multi-business-unit enterprise groups.
- Azure Solutions Architect Expert, CKA, CKAD, or TOGAF certification; computer vision or distributed systems publications, patents, or open-source contributions.
Working conditions
- Based in Abu Dhabi, UAE, with frequent international travel, primarily to India; travel increases during rollout waves and major releases.
- Site visits include retail, telecommunications, and industrial locations; industrial access requires safety induction and compliance with site HSE requirements.
- Work across time zones and provide escalation availability during major releases and rollout waves.
Success measures
The architecture is governed and followed, new domains are configured rather than rebuilt, and throughput and cost improve based on telemetry.
Fleet, site, and camera health are observable; onboarding is automated; releases are progressive and reversible; operational teams use documented runbooks.
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