Senior Applied AI Engineer - GenAI & Agentic Systems (Australia - Hybrid)

Technologies and Skills

• AI (Artificial Intelligence)
• LLM (Large Language Models)
• Event Driven Architecture
• Integration Testing
• Scikit-learn
• API Testing
• TensorFlow
• PyTorch
• Node.js
• Python
• MLOps
• CI/CD
• Azure
• React

Work Conditions

Work fully remote, globally.

About the Role

This position focuses on designing and operating production grade AI solutions specifically for the financial services sector. As a Senior Applied AI Engineer, you will bridge the gap between architectural design and secure, scalable implementation. Your work centers on generative AI, agentic workflows, and machine learning models, ensuring every solution meets the rigorous governance and regulatory standards of a highly regulated industry. Please note that we are only able to accept applications from candidates who are Permanent Residents of Australia who are able to successfully pass security clearance.

Most Important Requirements

• Senior Level Expertise with 5+ years in software, ML, or AI engineering and a proven track record of deploying systems into production.
• Strong Python Development skills coupled with a full stack context involving React and Node.js.
• Generative AI Proficiency through hands on experience building LLM based applications and RAG pipelines.
• Agentic System Engineering including the implementation of multi step workflows, tool integration, and stateful memory handling.
• Cloud and DevOps Foundations using at least one major platform such as AWS, Azure, or GCP alongside Docker and Git.
• Data and API Skills including SQL proficiency and the ability to build production APIs using REST or event driven services.
• Hours: Full-time (38 hours/week), with some flexibility to collaborate across global time zones.

Nice to Have

• Orchestration Frameworks such as LangGraph, AutoGen, or CrewAI.
• Enterprise Data Platforms including experience with Snowflake or Databricks.
• ML Framework Knowledge using PyTorch, TensorFlow, or scikit learn.
• MLOps and LLMOps experience specifically in model monitoring, drift detection, and latency optimization.
• Regulated Industry Experience within financial services or banking.
• Certifications at the associate level or higher for cloud platforms or Databricks.

Personal Traits

• Production Oriented focusing on building audit ready, monitored, and hardened systems rather than basic chatbots.
• Growth Mindset that inspires curiosity and is bold enough to challenge current thinking.
• Collaborative and Trustworthy in maintaining meaningful relationships with stakeholders and supporting colleagues.
• High Standards for Ethics prioritizing responsible AI practices such as explainability and bias awareness.
• Authentic and Playful bringing a positive attitude and respectful banter to a professional, laid back environment.

Our Hiring Process

1. Initial Interview (~1 week)

Skills Assessment (~1 week)

1. Interview with Partner (~1 week)

Additional Information: X-Team hires full-time contractors working standard 40 hours/week. Candidates handle their own taxes. Paid vacation is not offered but can be arranged.