About

Work Experience

• Software Engineer, NextGn Labs - Industrial Client

  May, 2024 - Present

  Provided end-to-end consultancy including business process design, product architecture, and technical implementation. Delivered data architecture and AI-driven applications for internal stakeholders

  • Built cloud-native Lakehouse architecture using Airbyte (GKE/AKS-equivalent), Snowflake, Dagster, DBT, Terraform, CI/CD using GitHub Actions with Docker/Kubernetes, and OpenMetadata for governance

  • Implemented MLOps pipelines (Dagster + MLFlow) for model retraining, anomaly detection, and growth forecasting with automated evaluation + monitoring

  • Developed LLM-powered chatbot, enterprise SharePoint RAG system, and custom React data views used by operational teams

  • Partnered with security teams to apply best practices, complying with strict data residency and network security principles, utilizing role-based access for masking, column-level and row-level security, and key management

  • Utilized DBT and Snowflake for dimensional and semantic modeling

  • Developed Generative AI automation workflows using agentic graph search, improving throughput and SLAs for factory production license processing

  • Improved system stability by resolving live AI agent and application issues, reducing failure frequency

  • Collaborated with data scientists to orchestrate feature extraction and training pipelines for ML models

  • Implemented LLM tracing, user feedback loops, and LLM-as-judge evaluation for quality control

  • Wrote test suites and Postman collections for REST API development, and performance tuning

• Software Engineer, NextGn Labs - Healthcare Client

  May, 2024 - Present

  Provided end-to-end consultancy including business process design, product architecture, and technical implementation. Delivered document processing systems with OCR and MLOps capabilities

  • Built document OCR ingestion pipelines with identity extraction, entity validation, and reconciliation against operational databases

  • Developed full MLOps lifecycle for OCR accuracy assessment with automated threshold-based alerts and monitoring dashboards

• Software Engineer - Ads Knowledge and Information, Google LLC

  May, 2022 - Mar, 20241 year 10 months

  Developed large-scale distributed batch data pipelines processing billions of Ads events daily

  • Developed large-scale distributed batch data pipelines processing billions of Ads events daily, written in C++ and SQL-based distributed execution systems

  • Integrated GDPR compliant data handling including wipeout, k-anonymity enforcement, and differential privacy

  • Collaborated with privacy-oriented horizontal teams to update governance compliance in legacy pipelines

  • Managed and monitored compute and storage resources for petabytes of cross-region pipelines and datastores

  • Implemented developer tooling for near real-time experiments with production-like LLM inference services in Jupyter notebooks, enabling rapid analysis of semantic embedding quality

  • Consolidated impressions log processing pipelines, ensuring smooth migration and continued quality via unit testing, metrics aggregation, and threshold-based alerting

  • Implemented centralized pipeline monitoring system for multiple adjacent teams, producing detailed long-term data quality metrics to augment team decision-making and reduce maintenance overhead

  • Participated in on-call rotation, resolving live incidents and ensuring continuous delivery of critical Ads systems

Skills

Education