Mohit Nagpal

Software Engineer

Bellevue, Washington, United States12 yrs 5 mos experience

Highly StableAI Enabled

Key Highlights

Led projects improving latency by 15x at Microsoft.
Designed observability pipeline handling 1B events daily at Uber.
Focused on driving Gen AI adoption and mentoring engineers.

Stackforce AI infers this person is a SaaS expert with strong capabilities in systems engineering and AI integration.

Contact

Skills

Core Skills

Data EngineeringObservability PipelinePolicy EnforcementCloud ArchitecturePerformance OptimizationData ScalabilityMicroservices ArchitectureThreat IntelligenceSignal ProcessingDatabase PartitioningPerformance TuningData IngestionFailover OptimizationStorage Management

Other Skills

.NETAlgorithmsCC#C++Core JavaCost OptimizationCross-functional CoordinationData PipelinesData StructuresDebuggingDebugging EfficiencyGen AIGenerative AIHTML

About

Over the past 14 years, I’ve built my career around solving complex engineering problems at scale, from designing fault-tolerant data systems at Microsoft to leading innovation at Uber. My journey has been driven by curiosity, precision, and a commitment to transforming ambiguity into elegant, scalable architecture. At Uber, I worked on the design of observability pipelines and policy enforcements platform. Before Uber, I spent a decade at Microsoft, shaping systems within Office 365 and Azure that scaled to millions of users worldwide. I led projects that improved latency 15x, expanded data export capabilities 40x, and built distributed solutions that redefined reliability and performance standards. My work sits at the intersection of systems engineering, AI integration, and technical leadership, creating solutions that not only scale efficiently but also deliver measurable impact. I believe the most powerful engineering comes from pairing deep technical rigour with empathy for the end user. Today, I’m focused on driving Gen AI adoption, enabling teams to build smarter, more adaptive systems, and mentoring engineers to think beyond code, to design for impact, clarity, and purpose.

Experience

Uber

Staff Software Engineer

Mar 2022 – Present · 4 yrs · Seattle, Washington, United States

Worked on designing and implementing a observability pipeline to support high-cardinality alerting. The pipeline consumes ~1B events daily and generates real-time alerts for and help in reducing mitigation time from one day to under an hour.
Designed a generic policy enforcement platform based on Google-CEL expression language. The platform onboard generic pre-flight checks

Data EngineeringPolicy EnforcementGenerative AIWorkflow AutomationObservability PipelineProcess Optimization

Microsoft

4 roles

Principal Software Engineer

Promoted

Mar 2021 – Mar 2022 · 1 yr

Served as Tech Lead for the customer adoption blocker team; designed and implemented a distributed lock service solution for policy-based retention applications across Exchange, SharePoint, and Teams. Reduced customer issues by 96% and improved latency by over 15x, unlocking $15M yearly revenue through increased customer acquisition.
Designed Spark and Azure Batch-based scalable architecture supporting a 40x increase in eDiscovery data export, contributing $12M in additional gross revenue through new E5 license offerings.

Cloud ArchitectureData ScalabilityPerformance OptimizationRevenue EnablementTechnical Leadership

Senior Software Engineer

Promoted

Jun 2017 – Mar 2022 · 4 yrs 9 mos

Designed and implemented a COGS-efficient signal-sharing system between Office and partner apps (Teams, SharePoint) operating on a scale of 50B signals and achieving 90% COGS efficiency improvement.
Developed a microservices-based architecture for the Automated Incident Response (AIR) feature for the Office 365 Threat Intelligence product, managing 1M investigations and analyzing 50M records daily, saving ~5M man-hours every day.

Microservices ArchitectureSignal ProcessingCost OptimizationThreat IntelligenceLarge-scale Systems

Software Developer Engineer

Promoted

Jun 2016 – Jun 2017 · 1 yr

Designed a database partitioning solution to store up to 1B rows per day.
Developed an ElasticSearch pipeline using Nest client for efficient data ingestion and optimized throughput, reducing CPU usage by 50% during high traffic.
As a side project, improved debugging time for threat intel features by 95% through real-time ElasticSearch index logging.

Database PartitioningData IngestionPerformance TuningDebugging EfficiencyScalable Architecture

Software Developer Engineer

Jul 2011 – Feb 2014 · 2 yrs 7 mos · Hyderabad Area, India

Optimized RTO for failover flows handling storage logical units in parallel, reducing failover time by 10x.
Represented Microsoft at SMIS Plugfest 2014 in Huawei Research Centre, Chengdu, China, collaborating with vendors including EMC, NetApp, and Huawei.

Failover OptimizationStorage ManagementVendor CollaborationCross-functional Coordination