Senior AI-Native Systems Engineer for Production

Accenture PLC; Miami (FL); On-site; USD 120,000 - 260,000; Full time

Job summary

Accenture PLC is seeking a senior software engineer to design, build, and operate end‑to‑end production systems across the full stack, including AI components and cloud infrastructure. You will own architecture, deployment, and security controls, partnering with cross‑functional teams to ship scalable, trustworthy software.

You will lead multi‑disciplinary engineering efforts, drive engineering standards, and push for reusable patterns while remaining hands‑on to inspect, prototype, and debug

Qualifications

• Minimum of 5 years of professional software engineering experience building and operating production systems.
• Minimum of 5 years spanning multiple layers of the stack, including front end or API through services, integration, persistence, and asynchronous processing.
• Minimum of 5 years of programming experience in at least one major language such as Java, Python, Go, TypeScript/JavaScript, or C#.
• Minimum of 5 years of hands‑on production experience with a major cloud platform (AWS, Azure, or GCP), including containers and orchestration (Docker, Kubernetes) and infrastructure as code (Terraform, Helm, or equivalent).
• Minimum of 5 years of experience designing and operating CI/CD pipelines through to production, including automated testing and integrated security controls.
• Minimum of 1 years of hands‑on experience designing, building, and deploying AI‑enabled or agentic systems in production or near‑production environments, including model integration, tool use, retrieval, context engineering, orchestration, and evaluation.
• Minimum of 1 years of experience applying AI‑native engineering tools and workflows to day‑to‑day software development, including code generation, automated testing, debugging, modernization, and documentation.
• Minimum of 5 years of experience leading engineering teams or significant technical workstreams, including leading client‑facing technical discussions, workshops, or delivery sessions under ambiguity.
• Bachelor's degree in Computer Science, Engineering or equivalent OR equivalent (minimum 12 years) work experience.

Responsibilities

• Design and build production systems across front end, APIs, backend services, integration, data, infrastructure, and AI components.
• Diagnose production issues wherever they live: application code, networks, infrastructure, identity, data, or AI workloads.
• Design and deploy workloads using containers, Kubernetes, serverless, managed cloud services, and infrastructure as code.
• Use the native capabilities of AWS, Azure, or GCP, including cloud networking, compute, storage, identity, secrets, service communication, and workload isolation.
• Build the automated path from commit to production: CI/CD, automated testing, security scanning, artifact management, infrastructure deployment, policy enforcement, and release controls.
• Engineer Data and Context architectures for AI systems, including retrieval, embeddings, metadata, knowledge sources, and privacy by design.
• Design and implement AI capabilities using frontier and enterprise models, integrated into live enterprise systems and production workflows.
• Lead multidisciplinary teams spanning software, cloud, platform, security, data, and AI engineering; set engineering standards and develop the engineers around you.
• Convert lessons from delivery into reusable patterns, tooling, and standards.

Skills

Software engineering

Production systems

Cloud platforms

CI/CD

AI-enabled systems

Team leadership

Docker/Kubernetes

Security controls

Programming languages

Education

Bachelor's degree in Computer Science or equivalent

Tools

Docker

Kubernetes

Terraform

Helm

Job description

Accenture PLC is seeking a senior software engineer to design, build, and operate end‑to‑end production systems across the full stack, including AI components and cloud infrastructure. You will own architecture, deployment, and security controls, partnering with cross‑functional teams to ship scalable, trustworthy software.

You will lead multi‑disciplinary engineering efforts, drive engineering standards, and push for reusable patterns while remaining hands‑on to inspect, prototype, and debug