Senior AI-Native Systems Engineer

Accenture

Orlando (FL)

On-site

USD 140,000 - 260,000

Full time

2 days ago

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Job summary

Accenture is seeking a senior software engineer to design and operate production systems across frontend, backend, data, and AI components. You will work across cloud platforms, containers, and CI/CD pipelines, taking ownership from architecture to production.

Travel may be required as projects span multiple clients and teams. You will lead engineering initiatives, implement AI-enabled capabilities, and shape technical direction while staying hands-on to prototype and debug solutions in real

Qualifications

Minimum of 5 years of professional software engineering experience building and operating production systems.
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 year 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 5 years of experience leading engineering teams or significant technical workstreams, including leading client-facing technical discussions, workshops, or delivery sessions under ambiguity.

Responsibilities

Design and build production systems across front end, APIs, backend services, integration, data, infrastructure, and AI components, making architectural decisions across all of these concerns together.
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 (Terraform, Helm, or equivalent).
Build the automated path from commit to production: CI/CD, automated testing, security scanning, artifact management, infrastructure deployment, policy enforcement, and release controls.
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.