10 дней назад
Python Engineer - AI
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Python Engineer - AI (Python/LLMs): Building scalable business-critical applications and agentic workflows that automate internal operations and generate first-pass analysis with an accent on end-to-end ownership, production reliability, and AI-driven automation. Focus on designing agents that assemble data, identify likely causes, and present explainable outputs while balancing latency, throughput, scalability, and maintainability.
Location: Sydney, Australia
Company
is a research-driven trading firm that builds proprietary technology, quantitative models, machine-learning systems, and algorithms for global financial markets.
What you will do
- Develop, test, deploy, and maintain high-performance Python applications.
- Build agentic workflows that generate first-pass analysis for business teams.
- Design end-to-end agents that assemble relevant data, identify likely causes, and present outputs for expert review.
- Own the full development lifecycle, from requirements gathering and stakeholder feedback through production deployment.
- Use agentic coding tools while maintaining a high production-quality standard.
- Apply automated testing and frequent deployment to deliver incremental value.
Requirements
- At least 3 years of professional software engineering experience with a strong focus on Python.
- Experience shipping a real LLM- or agentic-tooling solution, such as an agent, workflow, or internal tool.
- Experience with automated testing and CI/CD pipelines.
- Strong communication skills and the ability to collaborate with cross-functional teams and non-technical stakeholders.
- Ability to balance latency, throughput, simplicity, scalability, and maintainability.
- Curiosity and willingness to learn; prior financial markets or trading knowledge is not required.
Culture & Benefits
- Join a small engineering team with significant ownership and direct feedback from internal users.
- Work with researchers, traders, and engineers in a collaborative, experimentation-driven environment.
- Build systems using modern engineering practices, advanced infrastructure, and real-time feedback.
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