B.Tech Electronics & Communication Engineering
GGSIPU Delhi.
Sydney, NSW - AI Engineer
Sumneet Kaur
I build AI systems that ship.
My background spans enterprise technology at Infosys and startup work at Kifaayat, where I build LLM workflows, RAG experiments, multi-agent pipelines, APIs, dashboards, and automation close to real users and business problems.
RAG Pipelines
Multi-agent Systems
FastAPI
LLM Infrastructure
The journey so far
A quick thread from electronics engineering to enterprise systems, Sydney, and production-minded AI engineering.
Technology Analyst, Infosys
Enterprise data and cloud systems.
Moved to Sydney
Started Master of Computer Science at the University of Sydney.
Kifaayat
Personalising marketing with LLM-powered user insights.
SafeMedAI and TeachSmart
Built clinical AI deployed on Railway, plus TeachSmart for a hackathon and Cambridge EduX 2026.
Graduated
Master of Computer Science, Data Science & AI, University of Sydney. Distinction, WAM 76.5.
Marketing intelligence
Building AI systems that turn social and user signals into next-best actions.
What I build
Multi-agent systems, RAG pipelines, production LLM infrastructure, and social signal tools that turn noisy behaviour into useful decisions.
AI Systems
- Hands-on experience with LLM systems, RAG pipelines, agent workflows, APIs, dashboards, and data products
- FastAPI services, Python pipelines, async workflows, embeddings, retrieval, and evaluation experiments
- LangGraph and multi-agent orchestration for turning messy signals into structured recommendations
- Strong intuition for where AI adds leverage, where evaluation is needed, and where simpler software wins
Production Delivery
- Enterprise foundations across Azure, AWS, CI/CD, Docker, Kubernetes, ETL pipelines, and REST integrations
- Startup operating experience across engagement systems, automation, internal tools, and reporting
- Written and analytical foundation from CS, AI/data science, NLP publications, dashboards, and research projects
- Commercial judgement from Kifaayat: growth loops, user behaviour, experiments, and impact measurement
Selected Work Gallery
A cinematic case wall of AI systems, growth experiments, retrieval pipelines, and social signal tools. Pick a card to open the episode notes.
Experience
Startup AI automation work layered on enterprise technical foundations.
AI Engineer
- AI ops Designed lifecycle, engagement, and follow-up automations using Zapier, AI APIs, and backend workflow orchestration.
- Growth Built contextual re-engagement flows from behaviour, market gaps, and activity signals.
- Data Shipped dashboards and reporting workflows for engagement trends, experiments, and startup performance.
50k+Social audience supported by engagement workflows and content systems
15k+Platform users reached through acquisition and lifecycle automation
23%Conversion improvement through segmentation and outreach experiments
60%Manual analysis reduced through AI reporting and dashboards
Technology Analyst
- Lead Led a 6-person team on an enterprise migration project, coordinating delivery across cloud, data, and release workstreams.
- Data Implemented ETL pipelines and REST API integrations for analytics and downstream platforms.
- DevOps Built CI/CD and deployment automation supporting containerised workloads across Azure and AWS.
6-personMigration team lead
3 yrsEnterprise delivery
MigrationWorkstream coordination
2 awardsDelivery recognition
Education
Computer science, data science, AI, and engineering foundations, anchored by postgraduate study at the University of Sydney.
Master of Computer Science - Data Science & AI
University of Sydney | Feb 2024 - graduated December 2025 | Distinction, WAM 76.5
Bachelor of Technology - Electronics & Communication Engineering
GGSIPU Delhi | 2016 - 2020 | CGPA 8.25/10
Publications
Research threads across NLP, sentiment analysis, IoT, automation, and ambient computing.
Literature Review of Twitter Sentiment Analysis
Published in an international open access journal. Surveys NLP techniques for sentiment classification on social media data, including feature extraction, model architectures, and benchmark patterns across Twitter datasets.
Read paperSmart Mirror: A Hub for Ambient IoT Environments
Conference paper on AI-powered gesture-controlled home automation using ambient IoT systems, presented at an international engineering conference.
Public link unavailableLet’s build useful AI systems.
Always happy to talk about LLM systems, agents, RAG pipelines, clinical and education AI, marketplace workflows, and social signal tools.