Nikhil Londhe

Product Engineer

Pittsburgh, Pennsylvania, United States4 yrs 11 mos experience

AI EnabledAI ML Practitioner

Key Highlights

Led a team to architect a cloud-native system.
Developed a recurring-events engine saving 11,600+ staff-hours.
Implemented automated testing, improving release cycles by 16%.

Stackforce AI infers this person is a SaaS-focused software engineer with expertise in cloud-native architectures and automated systems.

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Skills

Core Skills

Cloud-native ArchitectureEvent LoggingApi DevelopmentNode.jsJavaAutomated Testing

Other Skills

PythonDjangoProcess miningTypeScriptAgile MethodologiesSpring BootRegression testingApache AirflowPrompt EngineeringInformation RetrievalSearch EnginesMachine LearningRanking AlgorithmsOperating SystemsConcurrency

About

Software engineer with 5+ years of experience building scalable systems across enterprise, e-commerce, and B2B SaaS. I’m recent graduate of Master’s in Software Engineering program at Carnegie Mellon University. Reach out if you’re working on something technical, meaningful, and hard to solve.

Experience

4 yrs 11 mos

Total Experience

2 yrs 5 mos

Average Tenure

Current Experience

Carnegie mellon university school of computer science

Research Assistant

Mar 2026 – Present · 2 mos

Supporting research in AI-assisted software engineering by developing unified workflows for requirement elicitation, context ingestion, design and implementation planning, and iterative development with LLM-based tools
Contributing to the design and planning of new software engineering courses.

Surefront

Team Lead

Jan 2025 – Dec 2025 · 11 mos

Audit Logging & Process Analytics Platform
Led a 6-engineer team to architect a cloud-native audit logging and process mining system (Python, Django) processing 60M+ event logs/day, delivering real-time product change logs for executive clients.
Built a replicated event ingestion pipeline by instrumenting a single request hook across an 800K-line codebase, validating <10 ms/event latency overhead via load and failure-scenario stress tests, cutting root-cause analysis time 99%.
Architected a business analytics pipeline with optimized schema and query paths, enabling <1s aggregations on 100M rows and 99.9% uptime, reducing time-to-insight from weekly to real-time.

PythonDjangoCloud-native architectureEvent loggingProcess mining

Orah (previously boardingware)

Software Engineer 2

Apr 2022 – May 2024 · 2 yrs 1 mo

Core Product Backend
Led a 4-engineer team to launch self-serve trial onboarding (TypeScript, Node.js) with demo-data seeding, feature gating, and automated expiry and upgrade workflows, eliminating manual trial setup effort 100%.
Built a multi-tenant, cloud-native recurring-events engine using an RRULE-based recurrence model with per-instance overrides and asynchronous processing across 500+ schools, saving 11,600+ staff-hours.
Led a cross-team effort to ship Student Information System (SIS) sync APIs for Blackbaud by offloading updates to background workers and isolating integration logic from the core Events request path, processing 22K+ events/day.

TypeScriptNode.jsAPI DevelopmentAgile Methodologies

Lti - larsen & toubro infotech

Software Engineer

Jun 2019 – Apr 2022 · 2 yrs 10 mos

Engineering Productivity & Infrastructure
Implemented automated regression testing for an internal testing platform (Java, Spring Boot), adding built-in coverage analysis, speeding up release cycles by 16% for 10+ enterprise engineering teams.
Improved test quality and adoption of internal testing platform, raising test coverage from 20% to 97% and reducing post-release bugs by 60% by enforcing coverage standards and streamlining testing workflows.

JavaSpring BootAutomated testingRegression testing