Work expectations
Status
Actively looking
Not looking
Not looking
Open to new opportunities
Location
Sydney
-
Open to relocating
Commitment
Full-time, Casual / Contract / Part-time, Join as a startup co-founder, Internship
Availability from time of offer
Immediately
Development experience
1-2 years
Top 3 languages or frameworks
Python3, SQL, PyTorch
Also knows
Apache Kafka, Apache Spark, AWS, GCP, Azure
Preferred work environment
Hybrid, Fully remote, In the office
Strengths
I’m an AI and Data Engineer with 2 years of local Australian experience and a background in Aerospace Engineering , which gives me a unique mix of high-level technical logic and a disciplined approach to problem-solving. My core strength is building scalable, production-grade systems—whether it’s architecting serverless GCP pipelines that save over $10k in productivity or designing agentic RAG workflows to automate complex compliance audits. I’m at my best when I'm bridging the gap between data engineering and applied AI , using tools like Databricks, Azure, and Python to turn messy, high-volume data into clean, automated, and analytics-ready architectures. You should hire me to take the manual bottlenecks off your plate by building the reliable automation your team needs to scale.
Interested in working involving
Specially looking in AI and Data domain
Not interested in work involving
Nothing
Other information
I am an AI and Data Engineer with 2 years of local Australian experience and a focus on building production-grade automation that drives clear ROI. My core strength is bridging the gap between data engineering and applied AI, using tools like Databricks, Azure, and GCP to turn high-volume data into efficient, analytics-ready systems. I am particularly interested in the long-term impact of my work and am open to equity-based or stipend-heavy roles for the right project. You should hire me to eliminate manual bottlenecks and build the reliable, automated infrastructure your team needs to scale.
Able to work in Australia without visa sponsorship
Requires visa sponsorship to work in Australia
Pay expectations
Full-time
$
70000
per year
Casual / Contract
$
35
per hour
Pay is negotiable in exchange for equity
Pay is negotiable in exchange for equity
Pay is not negotiable in exchange for equity
Open to volunteering or working for equity only
Not interested in volunteering or working for equity only if joining as a co-founder
Work experience
Proudest professional achievement
One achievement I’m particularly proud of is building a serverless AI pipeline on Google Cloud Platform that completely automated a manual email triage process. Before this, the team was bogged down by a constant stream of operational emails, but I was able to architect a containerized Python app using Docker and GPT-4o to analyze and route these alerts in real-time.It wasn't just a technical win; it had a massive impact on our daily productivity, saving over $10,000 in reclaimed time per employee annually. This project really solidified my interest in the intersection of Data Engineering and AI, as I loved the challenge of using cloud-native tools to solve a frustrating, "human" problem. In the future, I want to keep building these kinds of autonomous systems that take the repetitive work off people's plates so they can focus on the bigger picture.
I am an AI & Data Engineer with 2 years of experience in the Australian market, specialising in building production-grade intelligence that drives actual ROI. My focus is on turning complex data into high-value automation—from serverless pipelines to autonomous agents.
I bring multicloud expertise across GCP (BigQuery, Cloud Run, Terraform) and Azure (Data Factory, Synapse Analytics), with heavy experience in Databricks, dbt Core, and DuckDB to build scalable, analytics-ready architectures. I specialise in Agentic RAG workflows using LangChain and LangGraph to automate complex decision-making.
I've architected solutions that automated 100% of manual triage processes and reduced legal assessment costs by 95%. I'm passionate about bridging the gap between technical engineering and business value.
I bring multicloud expertise across GCP (BigQuery, Cloud Run, Terraform) and Azure (Data Factory, Synapse Analytics), with heavy experience in Databricks, dbt Core, and DuckDB to build scalable, analytics-ready architectures. I specialise in Agentic RAG workflows using LangChain and LangGraph to automate complex decision-making.
I've architected solutions that automated 100% of manual triage processes and reduced legal assessment costs by 95%. I'm passionate about bridging the gap between technical engineering and business value.
Education
Master's in Data Science and Artificial Intelligence - University of Sydney
Bachelor's in Aerospace Engineering - M S Ramaiah University of Applied Sciences
Bachelor's in Aerospace Engineering - M S Ramaiah University of Applied Sciences
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