AI-Native Production Systems Lead Engineer

Accenture PLC; Hartford (CT); On-site; USD 94,000 - 273,000; Full time

Job summary

Accenture is seeking a senior software engineer to design and operate production systems spanning frontend, APIs, data, and AI. You will lead cloud-native platform development, containerized workloads, and secure, automated delivery pipelines for client deployments.

You will work with AI-enabled architectures, guide multidisciplinary teams, and maintain hands-on involvement to prototype, debug, and improve outcomes. Travel may be required for client work.

Qualifications

• Minimum of 5 years of professional software engineering experience building and operating production systems.
• Experience across front end or API through services, integration, persistence, and asynchronous processing.
• 5+ years in one major language (Java, Python, Go, TypeScript/JavaScript, or C#).
• 5+ years with a major cloud platform (AWS, Azure, or GCP) including containers and orchestration (Docker, Kubernetes) and IaC tools.

Responsibilities

• Design and build production systems across front end, APIs, backend services, integration, data, infrastructure, and AI components.
• Diagnose production issues in application code, networks, infrastructure, identity, data, or AI workloads.
• Design and deploy cloud workloads using containers, Kubernetes, serverless, and infrastructure as code.
• Lead CI/CD pipelines, automated testing, security controls, and release management.
• Design AI-enabled or agentic systems in production or near-production environments.

Skills

Software engineering

Distributed systems

Cloud platforms

CI/CD

Kubernetes

Security

Education

Bachelor's degree in CS/Engineering

Tools

AWS

Azure

GCP

Terraform

Kubernetes

Job description

Accenture is seeking a senior software engineer to design and operate production systems spanning frontend, APIs, data, and AI. You will lead cloud-native platform development, containerized workloads, and secure, automated delivery pipelines for client deployments.

You will work with AI-enabled architectures, guide multidisciplinary teams, and maintain hands-on involvement to prototype, debug, and improve outcomes. Travel may be required for client work.