Jahnavi N

I’m a Software Engineer with 4+ years full-time experience who enjoys building at the intersection of infrastructure, automation, AI, and developer experience. Most of my work revolves around simplifying complex systems whether that’s internal platforms, observability tooling, large-scale compute environments, or AI-driven workflows that make engineers’ lives easier.

I care a lot about building things that are actually useful, scalable, and thoughtfully designed not just technically impressive on paper. I enjoy taking ownership end-to-end: from messy ideas and whiteboard discussions to production rollouts and cross-functional execution.

Outside of the day-to-day work, I’m naturally curious and always exploring. Startup idea? Side project? Developer tool? AI experiment? Podcast concept? I’m usually the person excited enough to say “let’s build it” before overthinking it.

I don’t believe anyone knows everything in tech and honestly, that’s the fun part. I’m always willing to learn, adapt quickly, and put my full energy into solving interesting problems with good people.

• Built centralized infrastructure observability and automation platforms supporting 3K+ compute nodes and virtualization workloads, enabling real-time monitoring, anomaly detection, and operational analytics across large-scale infrastructure environments.
• Developed internal infrastructure asset lifecycle and inventory management platforms managing operational visibility and workflows for 500+ infrastructure assets across compute and virtualization environments.
• Built AI-powered infrastructure assistants using LLMs, RAG pipelines, LangGraph orchestration, and Claude Skills workflows, indexing 15K+ operational documents, logs, and infrastructure knowledge entries to improve troubleshooting efficiency and developer productivity.
• Implemented AI-driven operational workflows leveraging Claude Skills and MCP-based integrations for automated diagnostics, observability lookups, job analysis, and infrastructure support automation.
• Led data center infrastructure expansion and rack optimization initiatives across multiple high-density lab environments, improving rack capacity, smart PDU power visibility, and long-term infrastructure scalability for critical compute systems.
• Designed and developed LiveOps Anomaly Radar, a real-time anomaly detection and operational analytics platform which can analyze 1000s of events and behavioral signals using ML-driven insights in production workflows.
• Built intelligent job scheduling and infrastructure automation workflows improving resource allocation efficiency across environments handling thousands of concurrent compute jobs.
• Developed custom developer productivity tooling and VS Code extensions improving infrastructure debugging and job orchestration workflows for multiple critical engineering teams.
• Designed infrastructure utilization forecasting and host repurposing frameworks helping optimize usage across 200+ underutilized servers and compute systems.
• Led enterprise-scale infrastructure migration initiatives spanning thousands of physical hosts, VMs, and virtualization clusters with zero critical operational impact during rollout.
• Built machine learning-driven analytics applications including real estate prediction systems trained on 50K+ housing records, COVID-19 visualization platforms processing daily regional trend datasets, and IoT-based monitoring systems integrating multiple real-time sensor streams.