Top Tech Jobs & Startup Jobs

Lead development and deployment of large-scale machine learning models for Microsoft Ads, including ad selection and ranking, click prediction, auction simulation, demand intelligence, and advertiser outcome optimization. Apply deep learning, reinforcement learning, and causal inference, conduct online and offline experiments, improve model efficiency, and collaborate with research, engineering, data science, and product teams.

Investigate, troubleshoot, and resolve customer technical issues involving Windows operating systems, servers, patching, activation, BitLocker, deployment, and related infrastructure. Collaborate across teams, participate in technical communities, build product expertise through training, share knowledge, identify product defects, and escalate issues to support Microsoft product improvements.

Lead the architecture and delivery of hyperscale cloud infrastructure and deployment systems supporting Microsoft 365. Build secure, reliable, scalable distributed systems; drive automation, observability, security, compliance, and operational excellence. Influence technical strategy, mentor engineers, and collaborate globally to deliver platform investments and AI-enabled infrastructure capabilities.

Lead AI value realization for strategic customers by identifying value opportunities, building ROI and investment cases, defining KPI measurement frameworks, owning P&L tracking, and proving outcomes against baselines. Facilitate CFO-level workshops, quantify financial impact, develop reusable value frameworks and playbooks, and transfer value management practices to customer teams while collaborating across finance, strategy, engineering, product, and delivery.

Lead applied science for large-scale grounding, search, retrieval, ranking, and agentic AI systems. Develop and optimize models for relevance, source selection, tool use, multi-turn context, factuality, and grounded responses. Design evaluation frameworks and experimentation for retrieval quality, hallucination reduction, task success, latency, cost, and user satisfaction. Partner with engineering, research, product, and design teams to deploy improvements, influence architecture and product direction, and mentor technical teams.

Design, implement, and operate cloud-scale secure data access features for Azure Blob Storage. Lead end-to-end development, collaborate with stakeholders, improve availability, observability, performance, and apply AI-assisted engineering to enhance productivity and operations.

Serve as the technical lead and engineering advocate for strategic enterprise security customers. Manage high-severity incidents and escalations, coordinate mitigation and root-cause analysis, advise customers on Microsoft Security solutions, and communicate with executive stakeholders. Analyze telemetry and support trends, drive service improvement plans, influence product priorities, develop playbooks and readiness materials, and mentor peers. Participate in a shared 24x7x365 on-call rotation.

Design, build, and operate AI-first, cloud-native enterprise platforms and intelligent agents using LLMs and orchestration frameworks. Deliver APIs, microservices, event-driven systems, telemetry, and CI/CD pipelines; ensure security, compliance, reliability, and operational readiness. Collaborate with product, data science, and business stakeholders to translate requirements into scalable, production-grade solutions.

Establishes and operates an ongoing AI optimization framework for strategic customer engagements. The role improves workflows, adoption, prompts, enablement materials, and agent performance using Copilot, usage data, and behavioral signals. Responsibilities include detecting agent drift, prioritizing high-ROI investments, facilitating kaizen improvement cycles, embedding standard work and ownership, and transferring the capability to customer teams. The position also leads multidisciplinary teams and manages multiple projects or portfolios.

Design, develop, operate, and modernize reliable, scalable, secure backend cloud services supporting Microsoft 365 message delivery. Responsibilities include architecture, feature development, performance optimization, monitoring, incident resolution, production operations, engineering automation, testing, and use of AI-assisted development tools. Collaborate with engineering and partner teams to deliver end-to-end distributed systems solutions.