AI Native Software Engineering Manager

Accenture

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Remote

Quick summary

Work type: Remote
Location: Arlington, VAMilwaukee, WIKirkland, WACincinnati, OHNew York, NY
Salary: $94,400–$316,300 / yr
Employment: Full-time
Posted: 21 days ago
Freshness: Confirmed live today
Nearby: 99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $223k

This role $205k

$68k $343k

below market most similar roles pay here above market

This role pays less than 69% of similar roles. Most pay $195,000–$251,000 — the blue band above. At the midpoint, this role pays about $205k versus about $223k for comparable roles.

Based on 240 similar postings.

Employer

About Accenture

Accenture is a leading global professional services company specializing in IT, strategy, consulting, and operations, with a strong focus on digital transformation, cloud computing, and artificial intelligence.

Accenture currently has 174 open roles on FindRole.

Listed pay typically runs $94,400–$266,300 across 128 roles with salary data.

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At a glance

TL;DR · AI Native Software Engineering Manager

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The AI Native Software Engineering Manager joins a services company to build agent-powered workflows for enterprise clients. You will embed with customers to define use cases, prototype, and deploy robust, secure agentic workflows that integrate into complex environments. Key responsibilities include designing agent architectures for retrieval, orchestration, and policy-based routing, as well as developing abstraction layers for providers like Anthropic, Google, and OpenAI. You will utilize cloud-native technologies including Kubernetes, Docker, microservices, serverless, and event-driven architectures. Technical requirements include proficiency in Python or Java, CI/CD, Terraform, Helm, and RAG. You must possess expertise in designing production-grade agentic solutions, managing multi-provider pipelines, and leading technical workshops. This role solves the challenge of moving AI from experimentation to operational reality across finance, healthcare, and retail sectors.

Skills

Python Java RAG Kubernetes Docker Terraform Helm CI/CD Microservices Serverless OpenAI Anthropic Vertex AI Infrastructure as Code Observability Agentic Workflows

What you'll do

Design and engineer enterprise-ready AI agents featuring retrieval, orchestration, policy-based routing, and lifecycle observability.
Develop abstraction layers across multiple AI providers to enable seamless integration of various models into client systems.
Build scalable, cloud-native infrastructure using Kubernetes, Docker, microservices, and event-driven architectures.
Tailor and deploy agentic applications to solve specific problems in industries like finance, healthcare, and retail.
Lead design workshops and "code-with" sessions to define use cases and build trust with client stakeholders.
Establish evaluation plans and metrics to measure agent accuracy, latency, safety, and cost-effectiveness.
Create reusable patterns, documentation, and best practices to influence internal assets and client roadmaps.

What we're looking for

Bachelor's degree or equivalent (minimum 12 years) work experience; if an Associate Degree, minimum 6 years of work experience is required.
Minimum of 5 years of programming experience in Python, Java, or equivalent.
Minimum of 3 years of engineering experience with cloud-native systems including APIs, microservices, containerization, and serverless.
Minimum of 1 year of expertise in designing and deploying agentic solutions like RAG and orchestration in production environments.
Minimum of 2 years of experience with AI platforms such as OpenAI, Claude, and Vertex AI to build multi-provider pipelines.
Minimum of 5 years of experience deploying to production using CI/CD, infrastructure as code (Terraform, Helm), monitoring, and debugging.
Minimum of 5 years of experience with client communication, including leading technical workshops and delivering under ambiguity.
Experience in enterprise environments or with advanced agentic architectures is preferred; additional AI certifications are a plus.

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