Sep 2022 – Apr 2026 · 3 yrs 7 mos

• AI/AIOps
• Built production-grade AI/ML operational pipelines — delivering end-to-end model lifecycle management (data collection, training, deployment, monitoring, retraining) for anomaly detection and KPI analytics, enabling proactive incident prevention and operational forecasting.
• Deployed on-premises AI-focused metric storage solutions (Prometheus) integrated with Telegraf metric relays to support high-volume anomaly detection and time-series analysis at scale.
• Architected component and infrastructure mapping in Neo4j, integrating data from VMs, hypervisors, network devices, and storage — enabling faster root cause analysis and dependency resolution.
• Orchestrated and Lead AI-driven observability initiatives, including:
• Anomaly detection pipeline with noise reduction and actionable alerting.
• KPI analytics stack integrating ingestion, querying, and visualizations.
• Integration of AI agents with Thanos (Prometheus HA) metric stores using MCP server extensions.
• Observability/SRE
• Automated incident handling and alert correlation by integrating Argo Workflows with PagerDuty and WebEx, enabling faster incident triage and reducing manual operational workload.
• Scaled and optimized metrics pipelines through capacity benchmarking, load analysis, and performance tuning — enabling deployments to larger environments while improving throughput and stability.
• Engineered end‑to‑end Elastic Cloud automation using Terraform and PrivateLink/Kibana access controls, creating secure, repeatable deployments across multiple environments.
• Designed and deployed advanced observability dashboards in Grafana consolidating host metrics, process health, and system status — enabling Support teams to quickly assess service health.
• Participated actively in on-call rotations, addressing production issues across infrastructure and application layers; contributed to feature development and long-term maintenance of internal tooling and services.

Aug 2021 – Aug 2022 · 1 yr

• Building Observability as a Service by creating data pipelines for logs and metrics. Have experience deploying and configuring monitoring in both On-Prem (OpenStack) and Off-Prem (AWS) Infrastructures.
• Tech: Ansible/Terraform, CI/CD, Docker, Kubernetes/Nomad
• Telegraf, InfluxDB, Prometheus, Grafana, Kinesis/Kafka, ELK Stack

Feb 2021 – Jul 2021 · 5 mos

• Developed a tool for collecting and storing, capacity and utilization metrics of the On-prem Cloud
• Used data analytics tool to create business intelligence reports and predict future trends in these metrics
• Software: Python, GitLab CI/CD, MariaDB Galera Cluster, Tableau

Jul 2019 – Jun 2020 · 11 mos · Bangalore

May 2019 – Jun 2019 · 1 mo · Bengaluru Area, India

• Worked on team in charge for big data analytics and machine learning. Was tasked with hydration of data lake by moving data from an operational data store to the data lake. An inference engine was built based on this data lake for providing predictions for chronic health conditions.