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Leads technical strategy and execution for enterprise AI products and platform capabilities. Translates customer and business needs into product priorities, influences architecture, coordinates cross-functional launches, and improves enterprise deployment, security, governance, adoption, and scalability. Partners with engineering, product, security, legal, design, and go-to-market teams while communicating risks, milestones, tradeoffs, and program health to senior leadership.

Leads complex technical programs that integrate AI safety safeguards across ChatGPT, API, enterprise, cloud, and platform environments. Responsibilities include roadmap development, cross-functional execution, deployment readiness, risk mitigation, safeguard implementation, misuse prevention, monitoring, enforcement, metrics, and executive communication. The role partners with engineering, research, product, operations, legal, policy, and external stakeholders to deliver responsible AI deployments.

Design, build, evaluate, and deploy AI systems for enterprise customers. Responsibilities include creating prototypes and production integrations, diagnosing implementation issues, making decisions about reliability, security, governance, latency, cost, and safety, and helping customers scale adoption. The role also develops reusable architectures, tooling, playbooks, and technical guidance while partnering with customer and internal engineering, product, research, security, and go-to-market teams.

Design, build, evaluate, and deploy AI systems for enterprise customers, taking solutions from opportunity identification and architecture through prototyping, production launch, and scale. Responsibilities include coding, debugging, integrations, evaluation harnesses, reliability, observability, security, governance, latency, cost optimization, and customer adoption. The role also creates reusable architectures and tooling while collaborating with customer engineering teams and internal Product, Research, Engineering, Security, and go-to-market teams.

Owns end-to-end finance for assigned hardware COGS and inventory areas, including forecasting, financial close, variance analysis, inventory planning, and margin insights. Partners with Product, Supply Chain, Operations, Accounting, Systems/Data, and Finance teams to improve financial data, dashboards, controls, processes, and scalable workflows. Develops scenarios and recommendations, identifies risks and tradeoffs, and influences senior stakeholders without formal authority.

Lead Ads revenue accounting technical assessments and policy, establish governance and 0-to-1 processes, translate accounting into product/billing/data requirements, own reconciliations, accruals, controls, and audit-ready documentation while partnering cross-functionally to scale Ads monetization.

Lead strategy for webinars and digital events to drive qualified demand and pipeline. Own audience prioritization, portfolio design, programming, measurement, and conversion paths. Partner cross-functionally on production, promotion, qualification, and follow-up to translate engagement into sales-ready pipeline.

Lead end-to-end technical programs to deploy OpenAI models on major cloud partners. Own integrated roadmaps, launch readiness, partner engineering coordination, risk management, and build repeatable launch pipelines across cross-functional teams.

Lead high-stakes technology negotiations from strategy to signed agreement for data platforms, infrastructure, observability, and enterprise SaaS. Develop fact-based negotiation plans, align cross-functional stakeholders, shape complex commercial structures (cost, equity, revenue, risk), advise executives, manage supplier engagements and escalations, and convert lessons into reusable playbooks and market intelligence.

The Partner AI Deployment Engineer will guide AWS engagements, shape technical strategy, build AI architectures, and mentor partners to drive successful AI deployments.