AI Solutions Architect

Fitzgerald Jenkins Recruitment; Sydney; Hybrid; AUD 150,000 - 200,000; Full time

Job summary

Boutique Financial Markets trading firm seeks an AI Solutions Architect for their Sydney CBD office (3-4 days in the office, 1-2 days from home). The role emphasizes leadership, collaboration and building agentic AI features from data to deployment within a tight, in-person focused team.

You’ll guide ML lifecycle, work across product, design and engineering, and own technical design while solving ambiguous problems with creativity and rigour.

Qualifications

• 5+ years of professional software engineering experience with at least one ML/LLM feature shipped to production.
• Experience with ML lifecycle: feature engineering, training, evaluation, and production tooling (MLOps).
• Hands-on exposure to LLM-based or agentic systems and the trade-offs in memory and context design.

Responsibilities

• Ship ML/agentic features from feature engineering to deployment and monitoring.
• Build agentic workflows: LLM selection, tool use, memory, context management, evaluation and guardrails.
• Develop and maintain APIs and integrations exposing capabilities to the platform.
• Use AI coding tools, write clean code, participate in code reviews and design with senior engineers.
• Translate business needs into technical requirements and tackle ambiguous problems with creativity and rigour.

Skills

Python

SQL

LLM/Agentic systems

ML Ops

AWS data services

APIs

Team collaboration

Education

Bachelor's degree in Computer Science or Machine Learning

Tools

Git

Docker

API design

Cloud services (AWS)

Job description

Boutique Financial Markets trading firm seeks AI Solutions Architect for their Sydney CBD office (3-4/days in the office, 1-2 days from home).

Excellent leadership & collaborative culture!

Machine Learning and agentic products

• Ship machine learning and agentic features into solutions from feature engineering and model selection through to deployment and monitoring.
• Build agentic workflows: LLM selection, tool use, memory and context management, evaluation and guardrails.
• Develop and maintain the APIs and integrations that expose these capabilities to the wider platform.

Engineering practice

• Use AI coding tools in your everyday workflow and help the team refine how we build with them.
• Write clean, maintainable code, take part in code reviews and collaborate with senior engineers on technical design.
• Work with product managers and designers across the full delivery lifecycle.
• Translate business needs into clear technical requirements and tackle ambiguous problems with creativity and rigour.
• Troubleshoot and improve existing systems, and suggest better tools, processes and technologies.

About You

You’re a curious, self-motivated engineer who cares about the people outcome as much as the code, and enjoys solving problems in a small, collaborative team.

You’ll bring:

• 5+ years of professional software engineering experience, with at least one machine learning or LLM-based feature shipped to production.
• Working knowledge of the ML lifecycle: feature engineering, training and evaluation, and the tooling that keeps models running in production (MLOps).
• Hands‑on exposure to LLM-based or agentic systems. You can explain the trade‑offs in model selection, memory and context design, tool use and evaluation. Deep specialism isn’t expected; real experience and curiosity are.
• Python and SQL. Experience with AWS data services (Glue, S3, Iceberg or similar) and MySQL/MariaDB is a plus.
• A tertiary qualification in Computer Science, Machine Learning etc.
• Comfort using AI tools to accelerate your own development.
• A self‑starter with product thinking.
• Team player who enjoys collaborating in in‑person in the office - the right cultural fit is key!
• Clear communication, strong teamwork and a drive to own your work.
• Full Australian working rights.