Lead Microservices & AI Technical Architect

Powerdata Group Consulting; Canberra; On-site; AUD 180,000 - 260,000; Full time

Job summary

Powerdata Group Consulting seeks an experienced Lead Microservices & AI Technical Architect to shape enterprise cloud-native platforms and AI-enabled engineering across a major transformation program. You will set architectural direction, govern standards, mentor teams, and ensure secure, scalable, and resilient solutions aligned with business objectives.

You will lead the adoption of AI in the SDLC, drive modernization across containers and event-driven patterns, and collaborate with executives

Qualifications

• Extensive experience designing and governing cloud-native, microservices & event-driven architectures.

Responsibilities

• Provide architectural leadership for cloud-native, microservices, and AI-enabled platforms.

Skills

Cloud-native architecture

Microservices architecture

AI-enabled engineering

DevSecOps

CI/CD

Observability

Stakeholder leadership

Tools

Kubernetes

OpenShift

AKS

EKS

GKE

Job description

Lead Microservices & AI Technical Architect

Security Clearance:Must have Baseline Clearance

About the Role

We are seeking an experienced Lead Microservices & AI Technical Architect to provide strategic technical leadership within a major business application transformation program. This role will lead the establishment of the department's enterprise microservices and event-driven architecture capabilities while driving the adoption of AI-enabled engineering practices across the software development lifecycle.

You will play a pivotal role in shaping architectural direction, influencing engineering decisions, mentoring technical teams, and ensuring modern, secure, scalable, and resilient technology platforms are delivered in alignment with enterprise objectives.

Key Responsibilities

Enterprise Architecture & Technical Leadership

• Provide architectural leadership for the design, implementation, governance, and evolution of cloud-native, microservices-based, and AI-enabled platforms.
  
• Ensure solutions align with enterprise architecture standards, cybersecurity requirements, business objectives, and digital transformation strategies.
  
• Define and govern architectural patterns, standards, reference models, and reusable frameworks.
  
• Lead the adoption of AI-enabled software engineering practices across the SDLC.
  
• Drive the implementation of enterprise AI capabilities, including machine learning, semantic search, intelligent automation, and responsible AI practices.
  
• Establish governance frameworks supporting secure, ethical, and effective AI deployment.
  
• Lead modernization initiatives focused on cloud-native architectures, microservices, containerisation, and event-driven integration.
  
• Establish and enhance DevSecOps, CI/CD, automated testing, observability, monitoring, and platform engineering capabilities.
  
• Promote reusable engineering patterns that improve scalability, maintainability, reliability, and operational resilience.
  
• Provide strategic technical direction for enterprise transformation initiatives.
  
• Influence architecture decisions and technology roadmaps across multiple programs and stakeholders.
  
• Drive improvements in engineering maturity, service reliability, performance, and operational efficiency.
  

Stakeholder Engagement & Capability Development

• Build strong relationships with executives, business leaders, delivery teams, and technology partners.
  
• Lead multidisciplinary technical teams and foster a culture of collaboration, innovation, and continuous improvement.
  
• Provide mentoring, coaching, governance, and capability uplift to strengthen organisational technical maturity and knowledge transfer.
  

Requirements

• Extensive experience designing and governing cloud-native, microservices, and event-driven architectures in large enterprise environments.
  
• Demonstrated expertise delivering AI-enabled solutions, enterprise AI capabilities, machine learning, semantic search, and responsible AI frameworks.
  
• Strong background in software engineering, platform engineering, DevSecOps, CI/CD, automated testing, observability, and security-by-design.
  
• Proven success leading large-scale technology modernisation and digital transformation programs.
  
• Outstanding stakeholder management, communication, and leadership skills, with experience influencing executives and leading multidisciplinary teams.
  
• Hands-on experience with container platforms including Kubernetes, OpenShift, AKS, EKS, or GKE.
  
• Experience in cloud transformation, Site Reliability Engineering (SRE), platform engineering, observability tooling, and enterprise automation.
  
• Experience leading Agile delivery teams across geographically dispersed environments.
  
• Strong capability in coaching teams and driving engineering excellence and continuous improvement.