Top Tech Jobs & Startup Jobs in NYC, NY

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.

Lead technical sales and customer advisory engagements for Azure cloud and AI solutions in financial services. Build trusted relationships with executives and architects, design secure and resilient architectures, conduct demonstrations and proof-of-concepts, address technical objections, guide migrations, and influence Azure adoption. Maintain expertise across Azure AI Foundry, GitHub, App Services, Databricks, and Fabric while mentoring peers and collaborating with engineering teams.

Lead worldwide partner performance and growth by developing strategic partner business and go-to-market plans, driving co-sell execution, aligning C-suite priorities, resolving escalations, enabling partner capabilities, and accelerating cloud consumption and revenue through cross-functional collaboration.

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.

Build software infrastructure for large language model pretraining and post-training, including benchmarking, evaluation, routing, and backend systems. Contribute to model architecture, data curation, training, inference, alignment, and RLHF. Gather insights for compute roadmaps, make data-informed architectural decisions, and deliver iterative AI products in a fast-paced environment.

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.

Set the vision and roadmap for AI-powered skilling products, translating customer insights into measurable learning experiences. Lead prioritization across content, platform, telemetry, privacy, cost, and compliance; partner with Design and Engineering to launch trustworthy LLM-powered features. Drive product quality, experimentation, adoption, retention, enterprise partnerships, and cross-functional execution across multiple squads.