6 days ago

Python Engineer - AI

IMC Trading

Sydney

6 days ago

Apply

IMC is seeking a Python Engineer - AI to join its Sydney Business Operations Engineering team. The role focuses on building scalable, business-critical applications and agentic AI workflows using Python, LLMs, and modern engineering practices. Requires 3+ years of professional software engineering experience with a strong Python focus and hands-on experience shipping LLM or agentic tooling.

Core AIHybridFull-timeMid LevelPythonLLMs

Python Engineer - AI

Apply

Core AIHybridFull-timeMid LevelPython

Salary

Not specified

Work Location

Sydney, New South Wales, Australia, AU

Work Model

Hybrid

Experience Required

3 years

Employment Type

Full-time

Experience Level

3+ years of professional software engineering experience

Core Qualifications

Technical (Must-have)

PythonLLMsAgentic toolingAutomated testingCI/CD

Soft Skills

CommunicationCross-functional collaborationOwnershipCuriosityWillingness to learn

Preferred Qualifications

Technical (Nice-to-have)

Financial marketsTrading

Key Responsibilities

•Develop, test, deploy, and maintain high-performance Python applications.
•Build agentic workflows that perform first-pass analysis, so our business teams start from a considered position rather than a blank page
•Design agents that work through a problem end to end — assembling the relevant data, identifying likely causes, and presenting something a subject-matter expert can interrogate
•Take ownership of end-to-end development, from requirements gathering through to production deployment
•Use agentic coding tools to move faster, while holding a high bar for what goes into production
•Apply strong automated testing practices and frequent deployment to deliver incremental value
•Balance trade-offs between latency, throughput, simplicity, scalability, and maintainability in a complex technology landscape.

PythonAILLMAgenticFinancial ServicesTradingEngineeringHybridSydneyFull-time

Key Responsibilities

•Develop, test, deploy, and maintain high-performance Python applications.

•Build agentic workflows that perform first-pass analysis, so our business teams start from a considered position rather than a blank page

•Design agents that work through a problem end to end — assembling the relevant data, identifying likely causes, and presenting something a subject-matter expert can interrogate

•Take ownership of end-to-end development, from requirements gathering through to production deployment

•Use agentic coding tools to move faster, while holding a high bar for what goes into production

•Apply strong automated testing practices and frequent deployment to deliver incremental value

•Balance trade-offs between latency, throughput, simplicity, scalability, and maintainability in a complex technology landscape.