AI-Native Platform Leader (Cloud, Data & AI)

Accenture PLC; Redmond; On-site; AUD 175,000 - 263,000; Full time

Job summary

Accenture PLC seeks a senior software engineer to design, build, and operate production systems across frontend, APIs, data, cloud, and AI components. You will own architecture end-to-end, with responsibility from design through production, including secure delivery and observability.

You will lead multidisciplinary teams, work with enterprise clients, and apply AI-native engineering practices to deliver measurable business outcomes. Travel 25–75% may be required.

Qualifications

• Minimum 5 years building and operating production systems.
• Hands-on experience across stack layers: frontend to services, integration, persistence.
• 5+ years in programming with Java, Python, Go, TS/JS, or C#.
• 5+ years with major cloud platforms (AWS/Azure/GCP), containers and orchestration.
• 5+ years designing and operating CI/CD pipelines to production, with automated testing and security controls.
• 1+ years building AI-enabled or agentic systems in production.

Responsibilities

• Design and operate end-to-end production systems across frontend, APIs, backend, data, and AI components.
• Diagnose production issues in code, networks, data, identity, or AI workloads.
• Lead cloud-native platform design and deployment with containers, serverless, and IaC.
• Build AI-enabled capabilities using OpenAI/Anthropic/Microsoft/Google/AWS models integrated into live systems.
• Lead engineering teams and set technical direction while remaining hands-on to inspect and prototype.

Skills

Production systems

Cloud platforms

CI/CD pipelines

AI-enabled systems

Programming languages

Education

Bachelor's degree in CS/Engineering

Tools

Docker

Kubernetes

Terraform

Helm

Job description

Accenture PLC seeks a senior software engineer to design, build, and operate production systems across frontend, APIs, data, cloud, and AI components. You will own architecture end-to-end, with responsibility from design through production, including secure delivery and observability.

You will lead multidisciplinary teams, work with enterprise clients, and apply AI-native engineering practices to deliver measurable business outcomes. Travel 25–75% may be required.