AI Native Software Engineering Senior Manager/Assoc Director

Accenture; St. Louis (MO); On-site; USD 120,000 - 150,000; Full time

Benefits offered by this job

Market-competitive benefits package

Job summary

Accenture is seeking an experienced AI Native Engineer in St. Louis, Missouri. You will design and build agentic workflows and cloud-native solutions for enterprise clients, leveraging your expertise in AI platforms and engineering best practices.

The ideal candidate has over 10 years of experience in engineering, including deep knowledge of API integrations and client collaboration. The role may involve travel as per business needs and offers a robust benefits package.

Qualifications

• Minimum of 10 years engineering experience with cloud-native systems (APIs, microservices, containerization, serverless).
• Proven expertise in designing and deploying agentic solutions in production environments.
• Experience with AI platforms including OpenAI, Claude, and Vertex AI.

Responsibilities

• Design and engineer enterprise-ready AI agents.
• Develop abstraction layers across AI providers.
• Leverage containerization and microservices to deliver scalable AI-native systems.

Skills

Cloud-native systems

Agentic solutions

Python

Java

CI/CD

Client communication

AI platforms

Education

Bachelor’s degree in Computer Science or Engineering

Tools

Kubernetes

Docker

Terraform

Job description

Overview

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.

Qualifications

• Minimum of 10 years engineering experience with cloud‑native systems (APIs, microservices, containerization, serverless).
• Minimum of 1 year of deep expertise in designing and deploying agentic solutions (agents, orchestration, context engineering, RAG, workflows) in production environments.
• Minimum of 7 years of experience with AI platforms — OpenAI, Claude, Vertex AI, plus open‑source models — including building abstraction layers to manage multi‑provider pipelines.
• Minimum of 10 years of experience programming in Python, Java, or equivalent; familiarity with evaluation tooling, logging, monitoring, and agent observability.
• Minimum of 10 years of experience deploying to production — CI/CD, infrastructure as code (Terraform, Helm), monitoring, and debugging.
• Minimum of 10 years of experience in client communication and collaboration, including being capable of leading technical workshops and delivering under ambiguity.
• Bachelor’s degree in Computer Science, Engineering, or equivalent; additional AI certifications or agentic tool experience is a plus.

Bonus Points If

• You’ve served as an Agentic AI Engineer in an Enterprise environment
• 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.

Note: Compensation and benefits vary by location and role. Accenture provides a market‑competitive benefits package. Travel may be required for this role; amount varies by business need and client requirements.

Employment Statements

Accenture is an Equal Employment Opportunity (EEO) and Affirmative Action Employer. See our Equal Employment Opportunity Statement for details. Applicants must have work authorization for employment in the United States. Some statements regarding accommodation and privacy are included in this posting as required by law.