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Leads engineering execution for an enterprise AI platform, owning architecture, backend and data workflows, reliability, AI engineering practices, hiring, and delivery processes. The role combines hands-on coding and technical leadership, including building distributed systems, establishing observability and release practices, recruiting engineers, and translating enterprise deployment feedback into reusable product capabilities.

Deploy Nexus enterprise AI software for customers, from technical discovery through production validation and handoff. Build integrations, Python and SQL transformations, notebooks, APIs, and automation; validate data pipelines and semantic models; resolve technical issues; document and stabilize deployments; communicate with customer stakeholders; and convert recurring deployment challenges into reusable engineering improvements.

Build and maintain Nexus, an enterprise AI implementation platform. Develop backend services, APIs, integrations, orchestration workflows, automated data pipelines, transformations, semantic models, validation processes, and governed lakehouse assets. Partner with AI engineers and enterprise customers to deploy solutions, resolve complex data and system requirements, and create reusable integrations. Ensure secure, monitored, recoverable, and repeatable deployments across customer environments.

Own the design and implementation of Azure platform infrastructure for secure, repeatable enterprise AI deployments. Build IaC modules, identity and security controls, networking, CI/CD automation, observability, reliability tooling, and customer environment automation. Partner with product engineers and enterprise teams to standardize deployments across complex Azure environments, including decisions involving containers, scaling, resilience, isolation, and cost.