AIXION LAB · CAREER SNAPSHOT

Quality engineering evolved into systems engineering.

A concise recruiter-facing translation of the work shown across Aixion Lab. The project evidence stays the same; this page makes the competencies easier to scan.

GitHub ↗
Current directionQA · Automation · Applied AI
Flagship workTradeBot · Control Core
Working styleEvidence-led systems
Public résuméLive web version

PROFILE

Engineering quality into the architecture.

Experience across manual and automated quality engineering expanded into APIs, software systems, real-time data, ML experimentation and autonomous-system governance.

The common thread is reliability: explicit state, testable contracts, visible failure modes and evidence behind decisions.

CORE COMPETENCIES

Quality engineering

Manual/automation QA, scenario design, regression thinking, failure analysis.

Automation

Selenium/Appium-style automation, workflow/RPA thinking, process reliability.

Software systems

Java, Python, APIs, service behavior, integration and architecture.

Data & AI

Real-time data, ML experimentation, evidence-bound autonomous systems.

FLAGSHIP WORK

TradeBot

Real-time market-data integration, evidence-bound research, risk/governance boundaries, live observation and failure recovery.

Competencies: Python · WebSockets · APIs · testing · observability · ML research · system architecture.

Review TradeBot →

Aixion Control Core

Governed orchestration across intent, context, agents, tools, policy, evidence and explicit human/system authority.

Competencies: agent orchestration · APIs · policy architecture · tool integration · state management · human-in-the-loop design.

Review Control Core →

RECRUITER HANDOFF

Review the evidence, then take a copy with you.

This page is the current public career snapshot. Use Print / Save PDF to export it from any modern browser; the system pages remain the deeper evidence source behind the summary.

Review systems →