Top Tech Jobs & Startup Jobs

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.

PhD interns analyze and improve machine learning algorithms, design experiments, prepare and evaluate large-scale datasets, and prototype scalable AI systems. They apply research techniques to product scenarios involving search, language models, recommender systems, geospatial intelligence, or personalization. Interns collaborate with Microsoft teams, interpret evaluation metrics, support feature development, and help productionize applied science solutions.

Advise U.S. Federal Civilian agencies on mission transformation, cloud and AI adoption, and modernization. Lead executive engagements, develop multi-year transformation roadmaps, identify AI opportunities, build strategic relationships, shape opportunity pipelines, and coordinate Microsoft, engineering, and partner resources. Translate customer insights into scalable industry patterns, product strategy, and measurable mission outcomes from vision through deployment.

Develops, reviews, and maintains secure, scalable software using AI-assisted development tools. Contributes to architecture, coding, testing, deployment, monitoring, incident response, and reliability improvements. Collaborates with stakeholders and partner teams to understand requirements, manage dependencies, and deliver reliable cloud services. Applies engineering best practices for security, compliance, performance, automation, telemetry, and safe releases.

Lead Microsoft’s enterprise Talent Platform strategy, roadmap, governance, adoption, and evolution. Partner with engineering, HR, analytics, and business stakeholders to deliver integrated talent experiences, reporting, AI-powered capabilities, and agentic solutions. Drive organizational change, platform readiness, data strategy, measurement, stakeholder alignment, and continuous improvement across global talent systems and initiatives.