Open to opportunities

Jannet A Ekka User

@jannetaekka

AI/ML engineer shipping production agentic systems. Patent-pending multi-agent trading AI on Google Cloud. 4+ yrs enterprise engineering at Deloitte.

India

Message

What I'm looking for

A forward-thinking team hiring AI-native engineers — where directing AI tooling well is treated as a skill, not a shortcut. I'm most useful where agents meet reliability: evaluation harnesses, agent QA, guardrails, observability, and getting prototypes to production. Remote, and I work well async with written context.

I build AI that runs in production — architecture, learning loop, cloud deployment and live operations.

My flagship project, Smart Money Trading, is a patent-pending multi-agent system trading 8 crypto futures pairs on Google Cloud: 33,000 lines across 153 modules with a 166-test suite, six specialist personas under a learned Judge, and a weekly retrain gated on statistical overfitting checks. Every decision ships with a plain-English reason.

I came to AI from 4+ years at Deloitte leading a QA automation team for Fortune 500 clients, which is the part I think matters most right now. Everyone is shipping agents; far fewer can tell you when one is wrong. I build evaluation, monitoring and honest failure handling in from the start — my systems refuse to act on data they cannot verify, and any substituted default raises a warning rather than passing silently.

I'm also deliberately resourceful. All of the above runs from one 16GB laptop, because I'd rather invest in good instructions, reusable skills and repeatable workflows than in hardware. I work AI-native: I direct the tooling, review everything it produces, and own the result.

Rank 1 in my PGP in AI/ML (UT Austin McCombs & Great Lakes, GPA 4.09/5), Google Cloud Gen AI Academy certified, and looking for teams building AI products that have to survive contact with the real world.

Experience

Work history, roles, and key accomplishments

Current

Founder & Sole Engineer

Current

Smart Money Trading

Mar 2026 - Present (5 months)

Designed and operate a patent-pending multi-agent trading AI on Google Cloud — 33,000 lines, 153 modules, 166 tests. Six specialist personas vote into a learned Judge; an Optuna optimiser and contextual bandit retrain it on real outcomes behind a CPCV/Deflated-Sharpe overfitting gate. Shortlisted top 101 of 1,500+ teams at the Google Cloud Gen AI Academy APAC hackathon.

Current

Founder & Sole Engineer

Current

Smart Money Trading (SMT)

Jan 2026 - Present (7 months)

Design, build, and operate a patent-pending multi-agent trading platform running continuously on Google Cloud under systemd with watchdog, auto-restart, and per-decision audit logging. Own the full lifecycle solo, including architecture, learning loop, evaluation gates, cloud deployment, incident response, and cost control.

Python Optuna scikit learn CatBoost BigQuery Vertex AI Gemini Cloud Run Cloud Functions Streamlit Cloudflare Workers Docker Pytest GitHub Actions Systemd RAPIDS CUDA WebGL

Independent AI Engineer

Freelance

Jan 2024 - Dec 2025 (1 year 11 months)

Won Best DeFi Application at the OpenServ × Hack2skill hackathon with a multi-agent blockchain analytics platform. Shipped VerseCanvas on Vertex AI, multi-agent assistants on Google ADK / MCP / AlloyDB deployed to Cloud Run, and applied AI projects. Delivered all while a full-time family carer and completing a PGP in AI/ML at Rank 1.

Google ADK MCP AlloyDB Vertex AI Gemini OpenServ SDK Cloud Run Streamlit Python Docker GitHub Actions

Lead Frontend Developer

AutoKorrekt

May 2024 - Jun 2025 (1 year 1 month)

Led frontend for an AI answer-evaluation platform for teachers. Built interactive PDF processing with coordinate-based text extraction over AWS Textract, a bilingual EN/DE feedback interface on Amazon Comprehend, and designed the ML data flow across S3, RDS and SageMaker. Scaled to 1,000+ concurrent submissions.

React Next.js TypeScript Python Django AWS EC2 S3 RDS Sagemaker Comprehend

Machine Learning Intern

Internship Studio

Jul 2024 - Aug 2024 (1 month)

Built a Random Forest model (R² = 0.252) predicting YouTube ad views from engagement metrics across a 15,000+ video dataset, packaged for integration with business dashboards to inform ad-revenue optimisation.

Python scikit learn Random Forest Data Analysis

Test Automation Engineer (Analyst)

Deloitte Consulting LLP

Aug 2019 - Jan 2023 (3 years 5 months)

Led a 6-member QA engineering team delivering automated testing frameworks and enterprise data-processing solutions for Fortune 500 clients. Built Selenium and Katalon Studio automation components that improved test execution efficiency by 83%, and Jenkins-based automated reporting cut manual analysis time by 75%.

Selenium Katalon Studio Python JavaScript Jenkins Salesforce SAP Hybris Tableau Jira Git

Test Automation Engineer (Analyst)

Deloitte

Aug 2019 - Jan 2023 (3 years 5 months)

Led a 6-member QA team for Fortune 500 clients including AT&T and HPE. Built Selenium and Katalon automation that improved test execution efficiency 83%, tracked quality across 343 components via Python and Tableau, and analysed 50,000+ SAP Hybris transactions. Jenkins reporting cut manual analysis 75%.

GenAI Applications Engineer

Self Employed

AI/ML engineer shipping production agentic systems end to end, including a patent-pending multi-agent trading AI and multi-agent assistants on Google ADK, MCP, and AlloyDB. Brings 4+ years of enterprise QA automation leadership at Deloitte to agent evaluation and monitoring.