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Full time

Technology

HK

Data and AI Architect

Halcyon KnightsMelbourne, Victoria🇦🇺AustraliaPosted 8 Oct 2026

Quick Overview

Seniority

Mid Senior

Employment type

Full Time

Work mode

Hybrid

Location

Melbourne, Victoria, Australia

Machine LearningGenerative AILLM

Job Description

Enterprise platform strategy and readiness

Experienced Data & AI Architect with a track record of designing and delivering enterprise-scale data, machine learning, generative AI and agentic-AI solutions.

Assesses enterprise platform readiness across the full data and AI landscape, including data foundations, ML and LLM services, enterprise knowledge, integration, AI controls, user experience, runtime orchestration and platform engineering.

Identifies platform gaps, constraints and technical risks; develops practical, prioritised recommendations to strengthen the client's data and AI platform.

Solution architecture and design

Defines end-to-end solution architectures for specific data, ML and AI use cases, balancing functional needs with the client's existing technology environment, architecture standards, security requirements and delivery constraints.

Designs reusable patterns for data access, retrieval and knowledge grounding, model and agent execution, enterprise integration, identity and access controls, observability, evaluation, resilience and operational support.

Works closely with client enterprise architects, platform teams, security and risk stakeholders, product owners and delivery teams to align solution designs with target-state architecture and roadmaps.

Delivery and engineering leadership

Understands the client's engineering practices, delivery lifecycle and maturity; guides teams to adopt appropriate development, testing, release, documentation, operational-readiness and governance practices.

Provides hands on technical leadership throughout delivery, including architecture decisions, design assurance, technical troubleshooting, and transition of solutions into production support.

Communicates complex technical choices clearly to both senior business stakeholders and engineering teams, articulating trade-offs, dependencies, risks and recommended decisions.

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