Main Purpose of Role

The DevOps Lead ensures the reliability, scalability, and performance of critical systems and services. This role bridges development and operations, fostering a culture of automation, resilience, and continuous improvement. The manager leads a team of SREs to apply best practices, manage incidents, and drive operational excellence.

Qualifications, Skills and Experience: 

• Bachelor’s degree in Computer Science, Engineering, or related field

• Proven experience in SRE or DevOps leadership roles

• Strong knowledge of:

  • Cloud platforms (AWS, Azure, GCP)

  • Container orchestration (Kubernetes, Docker)

  • Infrastructure automation (Terraform, Ansible, Jenkins, Lava)

• Expertise in programming languages (Python, Java)

• Proficiency with source control systems (GitHub Enterprise)

• Familiarity with monitoring tools: Prometheus, Grafana, PRTG

• Excellent communication and stakeholder management skills

• Experience with distributed systems and high-availability architectures

• Knowledge of security and compliance frameworks (ISO27001, SOC 2)

• Certifications in cloud technologies or ITIL

• Experience with Agile, Scrum, and Atlassian Jira

• Familiarity with Google Cloud AI & ML services, including:

  • Vertex AI (end-to-end ML platform)

  • AutoML (custom model training)

  • BigQuery ML (machine learning in SQL)

  • Cloud AI APIs (Vision, Natural Language, Translation)

  • TensorFlow on Google Cloud

Other Attributes

• Strategic thinker with strong problem-solving skills

• Ability to thrive in a fast-paced, evolving environment

• Collaborative and empathetic leadership style

Key Elements & Activities of the RoleLeadership & Team Development

• Be a hands-on leader who connects with direct reports, peers, and partners both operationally and strategically

• Provide technical leadership and coaching, maintaining credibility in systems engineering, tools, and DevOps

• Promote a culture of learning, collaboration, and continuous improvement through Agile and Scrum

• Ensure the team has development pathways, meaningful objectives, and KPIs aligned to a clear technology roadmap

Reliability & Performance

• Manage, optimise, and deliver Systems, DevOps, and ML Ops as a service to internal stakeholders

• Define, publish, and measure Service Level Objectives (SLOs) and Indicators (SLIs)

• Oversee incident response, service request fulfilment, change management, optimisation backlogs, and post‑implementation/incident reviews

• Deliver efficiencies through problem management, release management, and continuous improvement

• Leverage Google Cloud AI and other tools for predictive analytics and anomaly detection

• Focus on consumption and cost-to-serve via demand shaping, capacity planning, and environment governance

Automation & Efficiency

• Develop and propagate frameworks, pipelines, and system engineering templates across platforms

• Evangelise engineering practices, microservices, CI/CD, infrastructure-as-code, and security-by-design

• Partner with Technology, Delivery, and Support teams to ensure alignment between software development and platform engineering

• Drive automation initiatives to promote self-help and self-enablement, reducing manual effort

Cross-Functional Collaboration

• Build strong relationships with stakeholders across Technology, Engineering, Architecture, and Seeing Machines support services

• Work closely with development teams to design scalable and resilient systems

• Align priorities across engineering, product, and operations teams

Governance & Compliance

• Influence architecture and governance standards to balance innovation, scalability, and compliance

• Establish cloud governance policies, access controls, and compliance standards

• Ensure systems are aligned to Seeing Machines DR and BCP expectations

Monitoring & Observability

• Enable monitoring systems, standards, and services that support predictive and reactive responses

• Develop and publish dashboards showing system health across Seeing Machines

• Deliver information and reporting according to an agreed cadence

Key LiaisonsInternal

• Technology Division

• Enterprise Systems & Services Department

• Project Leads

• All SM senior stakeholders

External

• Product Vendors

• Service Providers

Qualifications, Skills and Experience:

• Bachelor's degree in Computer Science, Engineering, or related field
• Proven experience in SRE or DevOps leadership roles
• Strong knowledge of:
  • Cloud platforms (AWS, Azure, GCP)
  • Container orchestration (Kubernetes, Docker)
  • Infrastructure automation (Terraform, Ansible, Jenkins, Lava)
• Expertise in programming languages (Python, Java)
• Proficiency with source control systems (GitHub Enterprise)
• Familiarity with monitoring tools: Prometheus, Grafana, PRTG
• Excellent communication and stakeholder management skills
• Experience with distributed systems and high-availability architectures
• Knowledge of security and compliance frameworks (ISO27001, SOC 2)
• Certifications in cloud technologies or ITIL
• Experience with Agile, Scrum, and Atlassian Jira
• Familiarity with Google Cloud AI & ML services, including:
  • Vertex AI (end-to-end ML platform)
  • AutoML (custom model training)
  • BigQuery ML (machine learning in SQL)
  • Cloud AI APIs (Vision, Natural Language, Translation)
  • TensorFlow on Google Cloud

Other Attributes

• Strategic thinker with strong problem-solving skills
• Ability to thrive in a fast-paced, evolving environment
• Collaborative and empathetic leadership style