AI Engineer | Forward Deployed Engineer

FourQuarters Recruitment; Melbourne; On-site; AUD 140,000 - 210,000; Full time

Job summary

FourQuarters Recruitment is helping an Australian bank to scale practical AI by placing a hands-on, forward-deployed engineer. You’ll work directly with the CTO and Head of Technology to move AI ideas from first talks to live production.

You will scope high-value AI use cases, deploy LLM-powered solutions, and integrate with legacy banking systems across multi-cloud AWS/Azure environments, in a regulated setting.

Qualifications

• Strong software engineering skills with Python in production.
• LLM or ML solutions deployed to production, not just PoCs.
• Hands-on Snowflake experience with AWS and/or Azure.
• Comfort integrating with legacy and enterprise systems.
• Consulting-style, forward-deployed mindset with stakeholders.
• Regulated financial services experience preferred.

Responsibilities

• Identify high-value AI use cases across lending, operations, risk, and customer service.
• Build and deploy LLM-powered solutions, including agents and RAG pipelines.
• Integrate AI with core banking and modern platforms.
• Prototype quickly, prove value, then harden for production in a regulated bank.
• Advise senior stakeholders and help shape a growing AI engineering capability.

Skills

Python

Production ML

Snowflake

AWS/Azure

Legacy system integration

Stakeholder engagement

Tools

LangChain

LlamaIndex

Semantic Kernel

Amazon Bedrock

Azure OpenAI

Snowflake Cortex

Job description

Want to build AI that actually ships? Work directly with the CTO and Head of Technology?

Our client is an established (non-big4), Australian bank that's growing fast, both by winning new customers and by buying smaller competitors. Each acquisition brings new systems, data and customers, which makes this one of the most interesting places in Australian banking to build practical AI.

The role

This is a hands-on, forward-deployed engineering role. You'll sit close to the business, find where AI can make a real difference, and take solutions from first conversation to live production.

What you'll do

• Find and scope high-value AI use cases across lending, operations, risk, customer service and acquisition integration.
• Build and deploy LLM-powered solutions, such as agents, RAG pipelines (AI that answers from the bank's own documents and data), document intelligence and workflow automation.
• Integrate across traditional core banking and newer AI-native platforms.
• Build on Snowflake in a multi-cloud AWS and Azure environment.
• Prototype fast, prove value, then harden solutions for a regulated bank.
• Advise senior stakeholders and help shape a growing AI engineering capability.

What you'll bring

• Strong software engineering skills, with Python essential.
• LLM or machine learning solutions deployed into production, not just proofs of concept.
• Hands-on Snowflake experience, plus AWS and/or Azure.
• Comfort integrating with legacy and enterprise systems.
• A consulting-style, forward-deployed mindset: you're confident with stakeholders and focused on outcomes.
• An understanding of regulated environments, with financial services experience strongly preferred.

Nice to have:

• LangChain, LlamaIndex or Semantic Kernel, Amazon Bedrock, Azure OpenAI or Snowflake Cortex, and experience with M&A integration or core banking modernisation.

Why this role

• You'll work directly with the CTO and Head of Technology, with no layers in between.
• You'll have real, visible impact at a bank that's growing and investing in AI.
• You'll work across a varied mix of legacy and cutting-edge technology.