Career Timeline
Professional journey through AI/ML engineering and technical leadership.
Tech Lead — AI Labs
Angel One
Architected and deployed multi-agent wealth management platform for autonomous customer servicing, portfolio intelligence, and investment advisory.
- • Built planner-executor-reviewer agents with persistent memory, real-time market data retrieval, and ML-driven risk profiling
- • Autonomously resolved customer queries, generated portfolio rebalancing strategies, and recommended personalized investment actions
- • Improved engagement by 35% and increased portfolio diversification
- • Reduced advisor response latency by 60%
Tech Lead — AdTech
Amagi
Upgraded real-time ad delivery systems using edge ML models and autonomous optimization pipelines.
- • Improved CTR by 30% through dynamic ad inventory optimization
- • Increased viewer retention by 20% via low-latency personalization
- • Built autonomous optimization pipelines on PyTorch, Kubernetes, Snowflake, and Delta Lake
Lead Software Engineer — DataViz
Slintel
Architected NLP2SQL platform using fine-tuned LLMs to automate dashboard query generation.
- • Improved dashboard creation efficiency by 200%
- • Reduced dashboard load times by 3x through automated aggregation framework
- • Led design of automated aggregation framework that optimized query execution
Senior Software Engineer — Google Cloud
Designed self-healing experimentation infrastructure and scalable user analytics pipelines within Google Cloud.
- • Embedded ML-based flag conflict detection and rollback prediction in Mendel experimentation tool
- • Reduced code-induced failures by 25% and minimized hotfix cycles
- • Built scalable user analytics pipelines and automated A/B test orchestration
- • Achieved 7% boost in long-term retention and 10% in short-term engagement via behavioral clustering
Senior Software Engineer — Client Experience
Goldman Sachs
Architected real-time NLP platform for extracting behavioral signals from client communications.
- • Built real-time NLP platform using Apache Flink and transformer models
- • Created multi-task ranking models for urgency, sentiment, and response prioritization
- • Deployed retrainable APIs with automated evaluation pipelines for continuous model optimization
- • Reduced response latency and improved service consistency
Software Engineer — Location Products
Persistent Systems
Built ML-driven workforce optimization systems for route planning and task duration prediction.
- • Improved field productivity and reduced operational downtime through ML-driven optimization
- • Led migration of training and inference pipelines from SAS to PySpark
- • Delivered 10x reduction in processing latency while eliminating licensing costs