AI-Native Engineering Manager: Enterprise Agent Platforms

Accenture; Morristown (NJ); On-site; USD 101,000 - 316,000; Full time

Benefits offered by this job

Benefits package

Job summary

Accenture is seeking an AI Native Engineer with deep expertise in designing and deploying agentic systems for enterprise environments. You will embed with clients to design use cases, prototype rapidly, and deploy robust, secure agentic workflows across complex environments.

You will collaborate with stakeholders to shape playbooks for scalable AI-native engineering, utilizing Kubernetes, Docker, and cloud-native architectures. A strong focus on delivery under ambiguity is required.

Qualifications

• Minimum of 5 years engineering experience with cloud-native systems.
• Minimum of 1 year designing and deploying agentic solutions in production.
• Minimum of 2 years experience with AI platforms (OpenAI, Claude, Vertex AI, etc.).
• Minimum of 5 years programming in Python or Java; experience with evaluation tooling and observability.
• Minimum of 5 years production deployments—CI/CD, IaC, monitoring, debugging.
• Minimum of 5 years client communication and leading workshops.

Responsibilities

• Agent Architecture and Engineering: design enterprise-ready AI agents with orchestration and lifecycle observability.
• AI Platform Integration: build abstraction layers across AI providers for seamless integration.
• Cloud-Native Engineering: use containers, microservices, serverless, CI/CD, and observability.

Skills

Cloud-native

Agentic AI

Python/Java

CI/CD

AI platforms

Education

Bachelor's degree or equivalent

Tools

Kubernetes

Docker

Terraform

Helm

Job description

Accenture is seeking an AI Native Engineer with deep expertise in designing and deploying agentic systems for enterprise environments. You will embed with clients to design use cases, prototype rapidly, and deploy robust, secure agentic workflows across complex environments.

You will collaborate with stakeholders to shape playbooks for scalable AI-native engineering, utilizing Kubernetes, Docker, and cloud-native architectures. A strong focus on delivery under ambiguity is required.