Senior AI Agentic Engineering Leader

Accenture; Beaverton (OR); On-site; USD 130,000 - 240,000; Full time

Job summary

Accenture seeks an AI Native Engineer with extensive experience to design and deploy agentic AI solutions for enterprise environments. You will embed with clients as technologist and trusted advisor, prototype use cases, and scale agentic workflows across diverse industries.

Role emphasizes deployment of AI agents, integration across providers, and robust, secure systems with measurable performance. Travel may be required. This is a high-impact, technical leadership position at Accenture.

Qualifications

• Minimum 10 years' experience with end-to-end software engineering and SDLC expertise.
• Minimum 8 years' experience in the following: programming in Python, Java, or equivalent; familiarity with evaluation tooling, logging, monitoring, and agent observability.
• Deploying to production — CI/CD, infrastructure as code (Terraform, Helm), monitoring, and debugging.
• With client communication and collaboration, including leading technical workshops and delivering under ambiguity.
• Minimum of 3 years’ experience in cloud-native systems (APIs, microservices, containerization, serverless).
• With AI platforms — OpenAI, Claude, plus open-source models — including building abstraction layers to manage multi-provider pipelines.
• Minimum of 2 years hands-on experience designing and delivering Agentic AI solutions.
• Minimum of 1.5 years with semantic models, ontologies, knowledge graphs, or enterprise knowledge.
• Using coding agents and AI-assisted software development.
• Minimum of 1 year designing and deploying agentic solutions (agents, orchestration, context engineering, RAG, workflows) in production environments.
• 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 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

AI-native engineering

Cloud-native systems

Agentic AI

Python/Java

CI/CD

Client workshops

Education

Bachelor's degree or equivalent experience

Tools

Kubernetes

Docker

Terraform

Helm

OpenAI

Anthropic

Google AI

Job description

Accenture seeks an AI Native Engineer with extensive experience to design and deploy agentic AI solutions for enterprise environments. You will embed with clients as technologist and trusted advisor, prototype use cases, and scale agentic workflows across diverse industries.

Role emphasizes deployment of AI agents, integration across providers, and robust, secure systems with measurable performance. Travel may be required. This is a high-impact, technical leadership position at Accenture.