Samta
Balpande.
Senior Staff AI Engineer at GE Vernova, building production LLM systems and anomaly-detection architectures for the operations of critical infrastructure.
Where engineering meets reliability research.
— AIOps
— Anomaly detection
— LLM systems
— RAG & agents
— Causal inference
— Time-series modeling
I am a Senior Staff AI Engineer at GE Vernova, where I lead architecture for the enterprise AI and LLM platform powering mission-critical electric-grid operations. My work spans the full stack of production AI — from data and evaluation to deployment, observability, and cost/latency optimization.
Over the last seven years, I have shipped machine-learning systems for outage prediction at DTE Energy, price optimization at Staples, and LLM-driven operational intelligence at GE Vernova. Across those roles I have authored eleven publications on AIOps, anomaly detection, regulated CI/CD reliability, ethical AI, and platform engineering, and I am a named inventor on two filed patent applications.
I serve as a reviewer for IEEE international conferences and have been invited to speak at conferences hosted by Manchester Metropolitan University and the University of Essex.
Reliability AI for systems that cannot fail.
intersection of
machine learning,
site reliability,
and operations.
My research and engineering focus is the production reliability of intelligent systems operating in regulated, high-stakes environments — power grids, banking platforms, and industrial control rooms. I am especially interested in:
Anomaly detection on multivariate telemetry — designing models that surface meaningful weak signals from millions of daily events without drowning operators in false positives.
Agentic AIOps — building multi-agent orchestration that triages alerts, correlates evidence across systems, and produces audit-grade incident narratives suitable for regulated industries.
LLM systems engineering — making retrieval, evaluation, and inference reliable at scale, with grounded citations, drift monitoring, and cost-aware routing.
Eleven papers on AI for operations & infrastructure.
- AI-Powered Anomaly Detection for Real-Time Financial Platform Reliability Monitoring: Benchmarking Machine Learning Algorithms for Detecting Outages, Latency Spikes, and Security Violations in Banking.
- From Incident to Evidence: Autonomous AIOps for DORA-Ready Financial DevOps.
- A Reliability Control Plane for Regulated CI/CD: Integrating On-Call Triage, Risk-Tiered Release Governance, and Evidence-by-Design.
- From Alert Floods to Action: Correlated Telemetry for High-Volume Banking Systems.
- Graph-Based Control-Impact Modeling for Predictive Change-Risk Mitigation in Regulated DevOps Pipelines.
- Predictive Delivery Intelligence for Payments and Core Banking: Reducing Change Risk at Scale.
- Operationalizing Ethical AI in Financial DevOps: Balancing Intelligent Automation with Fairness and Accountability.
- Secure Hybrid Integration for Banking Platforms: Speed, Safety, and Regulatory Proof.
- Platform Engineering in Regulated Finance: Self-Service Without Losing Control.
- Exploring the Non-Medical Impacts of COVID-19 Using Natural Language Processing.
- Steganography Using Genetic Encryption Along with Visual Cryptography.
Named inventor on filed patent applications.
GE Vernova.
USPTO numbers
available on
request.
Peer review & professional service.
IEEE and
international
conferences.
Invited speaker
at UK
universities.
Seven years of applied ML in industry.
Retail.
Utilities.
Critical
infrastructure.
Trained in data science & computer science.
undergraduate
training.