Top Tech Jobs & Startup Jobs in Charlotte, NC

Lead customer engagements to qualify and close cloud and AI opportunities on Azure. Drive sales strategy, pipeline hygiene, partner co-sell, and AI-driven forecasting. Collaborate across account teams, enable customer adoption and consumption, and act as trusted advisor to accelerate AI and cloud transformations.

Lead design and build of production-ready cloud and AI systems, prioritize security and reliability, ship solutions quickly using modern engineering practices, collaborate with cross-functional teams, mentor engineers, drive customer adoption, and deliver reusable assets and end-to-end complex deliveries.

Develop forecasting models, scorecards, dashboards, and decision-support insights for AI and non-AI capacity. Analyze demand, supply, customer, and operational data to identify constraints, quantify risks, and recommend allocation or mitigation actions. Partner with Engineering, Finance, Data Science, Operations, and tooling teams to improve data quality, forecasting methods, reporting, and automation. Communicate trends, assumptions, risks, and recommendations through executive-ready presentations and narratives while standardizing analytical processes and best practices.

Leads Azure capacity automation and backend tooling programs across Engineering, Finance, Operations, and capacity planning teams. Translates business needs into requirements, user stories, acceptance criteria, and workflow specifications; manages dependencies, risks, governance, and delivery. Improves processes through automation, data analysis, reporting, and AI-powered solutions such as Microsoft Copilot. Drives stakeholder alignment, change adoption, data quality, documentation, and operational excellence across capacity allocation and prioritization workflows.

Customer-embedded principal data scientist who leads technical delivery for strategic accounts, builds production-grade solutions, translates business needs into technical approaches, influences senior stakeholders, and transitions work to FDE teams while operating in ambiguous, fast-paced environments.

Leads Microsoft's Global Business Operations team, overseeing executive operating rhythms, portfolio governance, cross-functional alignment, performance insights, and strategic execution. Establishes scalable operating models, drives AI-enabled process automation, communicates business impact to senior stakeholders, and ensures decisions translate into measurable outcomes. Manages, coaches, and develops a high-performing strategic operations team while improving cadence efficiency, accountability, and organizational adoption.

Own product strategy and multi-year roadmaps for GPU back-end networking. Translate AI workload needs into requirements, lead products through qualification and deployment, coordinate engineering and business teams, influence suppliers, and improve performance, reliability, cost, observability, and launch readiness.

Manages a portfolio of medium-enterprise customers, develops executive relationships, drives cloud solution adoption, and achieves revenue, consumption, renewal, upsell, and cross-sell targets. The role coordinates Microsoft teams and partners, qualifies opportunities, leads account and renewal strategies, uses digital CRM and sales tools, resolves customer issues, and provides customer and industry insights. It also requires maintaining expertise in Microsoft solutions, technology trends, and assigned industries.

Lead architecture and implementation of high-performance vector search and semantic retrieval across Azure data products. Mentor engineers, collaborate with research teams, ensure scalability, testability, performance, and production readiness of libraries and embeddings-based solutions.

Drive technical sales for Microsoft’s cloud and AI data platform through demos, proofs of concept, hackathons, and architecture workshops. Advise enterprise customers on secure, scalable database and analytics architectures, migrations, and deployments. Build relationships with platform leaders, resolve technical blockers, collaborate with engineering, and promote Azure data technologies including Fabric, Databricks, Purview, and Azure databases.