I build AI and software systems that make operational work more reliable, inspectable and safe. My work sits where backend engineering, applied AI, data and product delivery meet.
I am completing a Master of Computer Science (Advanced Entry) at the University of Sydney in November 2026.
- Guarded agentic systems with bounded tools, inspectable evidence and human review.
- Backend services and data workflows using Python, FastAPI, SQL and PostgreSQL.
- Applied ML systems with explicit evaluation, failure analysis and operational boundaries.
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Production-style AI engineering platform for RAG, guarded read-only SQL, bounded LangGraph agents, evidence verification and human review. Evidence: 114 backend tests, 9 frontend tests, 5 browser workflows and 40/40 deterministic evaluations of routing, tool safety and evidence integrity. This is not a live-model accuracy claim.
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Synthetic utility-data onboarding control plane for typed ingestion, reconciliation, data-quality gates and reviewable exceptions.
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Synthetic fleet-operations MVP combining governed KPIs, data-quality controls, ML and evidence-linked AI recommendations.
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Point-in-time-safe weather and day-ahead power-market research with chronological evaluation and cost-aware backtesting. Evidence: 51.6% lower final-holdout MAE than the declared seasonal-naive comparator, within the repository's stated research limitations.
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Synthetic asset-finance workflow with explicit BPMN and DMN decisions, resilient workers, human review and auditable state.
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Safety-first telemetry validation and explainable operating-window recommendations for human decision support.
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- Technical Co-Founder & Product Manager, KRSP Tech: stakeholder discovery, requirements, backend and product contribution, distributed delivery and release review.
- Machine Learning Intern, Defence Research and Development Organisation: contributed to a commercialised Intelligent Character Recognition System through Transformer OCR work covering 22 Eighth Schedule Indian languages plus English, using 22 million text-image pairs overall across data preparation, training, inference and evaluation.
- Master of Computer Science (Advanced Entry), University of Sydney: Artificial Intelligence, Data Science and Cybersecurity. Completing November 2026.
- Languages: Python, TypeScript, JavaScript, SQL, C#, R
- Backend and data: FastAPI, PostgreSQL, REST APIs, Pydantic, Docker, data pipelines
- AI and ML: LangGraph, RAG, Transformer models, NLP, model evaluation, error analysis
- Product and cloud: React, AWS, GitHub Actions, stakeholder discovery, release delivery
- Analyzing Public Sentiment Towards LLM: A Twitter-Based Sentiment Analysis, IEEE, 2024.
- An Integrated Framework for Securing Web Applications, JISEM, 2025.
- INFO6007 Best Project Award for AI-Powered Fraud Detection in Banking.
- Microsoft hackathon winner.
If your team is building applied AI, backend platforms or automation systems, connect with me on LinkedIn or email kishoresrinivasan05@gmail.com.