AI Native Software Engineering Manager

Accenture PLC; Redmond; On-site; AUD 213,000 - 327,000; Full time

Job summary

Accenture PLC is seeking an AI Native Engineer to design and deploy agentic workflows within enterprise environments. You will embed with clients as technologist and advisor, shaping use cases, prototyping rapidly, and delivering robust, secure AI agents that scale across complex infrastructures.

You will lead technical workshops, define metrics, and build reusable patterns and documentation to accelerate adoption and outcomes across industries. Travel may be required.

Qualifications

• Minimum of 3 years engineering experience with cloud-native systems.
• Minimum of 1 year expertise in designing and deploying agentic solutions (agents, orchestration, context engineering, RAG, workflows) in production environments.
• Minimum of 2 years experience with AI platforms — OpenAI, Claude, Vertex AI, plus open-source models — including building abstraction layers to manage multi-provider pipelines.
• Minimum of 5 years experience programming in Python, Java, or equivalent; familiarity with evaluation tooling, logging, monitoring, and agent observability.
• Minimum of 5 years experience deploying to production — CI/CD, infrastructure as code (Terraform, Helm), monitoring, and debugging.
• Minimum of 5 years experience with client communication and collaboration, including being capable of leading technical workshops and delivering under ambiguity.
• Bachelor's degree or equivalent (minimum 12 years) work experience. (If Associate Degree, must have minimum 6 years work experience)

Responsibilities

• Agent Architecture and Engineering: Design and engineer enterprise-ready AI agents encompassing retrieval, orchestration, policy-based routing, tool invocation, evaluation harnesses, and lifecycle observability.
• AI Platform Integration: Develop abstraction layers across AI providers (Anthropic, Google, OpenAI, etc. ) to enable seamless integration and enablement.
• Cloud-Native Engineering: Leverage containerization (Kubernetes, Docker), microservices, serverless, event-driven architectures, CI/CD, and observability to deliver scalable AI-native systems.
• Domain-Specific Workflows: Tailor and deploy agentic applications across verticals — e.g., finance, healthcare, retail — addressing domain-specific processes via intelligent automation.
• Client Engagement: Conduct design workshops, POCs, and code-with sessions to shape data-driven agent workflows with stakeholders, fostering trust and adoption.
• Measure & Improve: Define and use key metrics, test harnesses, and evaluation plans to measure agent accuracy, latency, safety, and cost effectiveness.
• Knowledge Sharing: Craft reusable patterns, documentation, and best practices to influence internal assets and client roadmaps.

Skills

Cloud-native systems

Python

Java

CI/CD

Terraform

Helm

Observability

Stakeholder engagement

Workshops facilitation

Agent orchestration

Education

Bachelor's degree or equivalent

Tools

Kubernetes

Docker

Job description

We are:

A forward-thinking services company at the forefront of AI-native innovation. We partner with enterprise clients to create next-generation, agent-powered workflows engineered to scale in real-world settings. Our engineers embed deeply with customers, moving projects beyond experimentation into operational reality.

You are:

An AI Native Engineer with a minimum of 5 years of experience building cloud-native solutions, and deep expertise in designing and deploying agentic systems, especially for enterprise environments. You are a critical thinker that thrives in ambiguity, delivering concrete results by designing, building, and running custom AI agents that augment workflows and scale across modern infrastructure. You’ll help shape the playbook for how enterprises adopt and scale AI-native engineering globally.

The Work:

You’ll embed directly with clients — acting as both technologist and trusted advisor. You’ll partner with stakeholders to define use cases, rapidly prototype, and deploy agentic workflows that are robust, secure, and operational in complex enterprise domains. Often, these will be completely net new platforms and systems that need to be stitched together in our clients' environments alongside our Ecosystem partners.

Responsibilities:

• Agent Architecture and Engineering: Design and engineer enterprise-ready AI agents encompassing retrieval, orchestration, policy-based routing, tool invocation, evaluation harnesses, and lifecycle observability.
• AI Platform Integration: Develop abstraction layers across AI providers (Anthropic, Google, OpenAI, etc. ) to enable seamless integration and enablement.
• Cloud-Native Engineering: Leverage containerization (Kubernetes, Docker), microservices, serverless, event-driven architectures, CI/CD, and observability to deliver scalable AI-native systems.
• Domain-Specific Workflows: Tailor and deploy agentic applications across verticals — e.g., finance, healthcare, retail — addressing domain-specific processes via intelligent automation.
• Client Engagement: Conduct design workshops, POCs, and code-with sessions to shape data-driven agent workflows with stakeholders, fostering trust and adoption.
• Measure & Improve: Define and use key metrics, test harnesses, and evaluation plans to measure agent accuracy, latency, safety, and cost effectiveness.
• Knowledge Sharing: Craft reusable patterns, documentation, and best practices to influence internal assets and client roadmaps.

Travel may be required for this role. The amount of travel will vary from 0 to 100% depending on business need and client requirements.

Here’s What You Need:

• Minimum of 3 years engineering experience with cloud-native systems (APIs, microservices, containerization, serverless).
• Minimum of 1 year expertise in designing and deploying agentic solutions (agents, orchestration, context engineering, RAG, workflows) in production environments.
• Minimum of 2 years experience with AI platforms — OpenAI, Claude, Vertex AI, plus open-source models — including building abstraction layers to manage multi-provider pipelines.
• Minimum of 5 years experience programming in Python, Java, or equivalent; familiarity with evaluation tooling, logging, monitoring, and agent observability.
• Minimum of 5 years experience deploying to production — CI/CD, infrastructure as code (Terraform, Helm), monitoring, and debugging.
• Minimum of 5 years experience with client communication and collaboration, including being capable of leading technical workshops and delivering under ambiguity.
• Bachelor's degree or equivalent (minimum 12 years) work experience. (If Associate Degree, must have minimum 6 years work experience)

Bonus Points If:

• You’ve served as an Agentic AI Engineer in an Enterprise environment
• Additional AI certifications or agentic tool experience is a plus.
• You’ve defined or worked with enterprise-grade architectures for compound AI systems, orchestration frameworks, or agent registry/stream-based architectures.
• You understand the AI-native paradigm — blending cloud-native with generative model architectures — optimizing for performance, modularity, and efficiency.
• You’ve delivered solutions across multiple industries (e.g., finance, healthcare) by tailoring agentic workflows to industry needs

Compensation at Accenture varies depending on a wide array of factors, which may include but are not limited to the specific office location, role, skill set, and level of experience. As required by local law, Accenture provides a reasonable range of compensation for roles that may be hired as set forth below. We anticipate this job posting will be posted until 11/20/2026.

Accenture offers a market competitive suite of benefits including medical, dental, vision, life, and long-term disability coverage, a 401(k) plan, bonus opportunities, paid holidays, and paid time off.

• medical
• dental
• vision
• life
• long-term disability coverage
• 401(k) plan
• bonus opportunities
• paid holidays
• paid time off

See more information on our benefits here: U.S. Employee Benefits | Accenture (https://www.accenture.com/us-en/careers/local/benefits)

California $94,400 to $316,300

Colorado $94,400 to $273,200

Connecticut $94,400 to $273,200

District of Columbia $100,500 to $291,000

Illinois $87,400 to $273,200

Maine $80,400 to $232,800

Maryland $94,400 to $273,200

Massachusetts $94,400 to $291,000

Minnesota $94,400 to $273,200

New York $87,400 to $316,300

New Jersey $100,500 to $316,300

Ohio $87,400 to $253,000

Virginia $87,400 to $291,000

Washington $100,500 to $291,000

#LI-MP

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