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# AI Engineer

- **Company:** Accenture
- **Location:** Alexandria, VA, United States
- **Salary:** $100,200.0 - $203,400.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Cyber Security, Information Engineering, Python (Programming Language), Performance Tuning, Multi-Agent Systems, Generative AI, AI Platforms, Kubernetes, Deployment Automation, Machine Learning Operations, Devsecops
- **Published:** May 27, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=f58285b1ca007ef7

## About the Role

Do you have experience in Python?, * Experience AI/ML production engineering, LLMOps or MLOps, and the deployment of Retrieval-Augmented Generation (RAG) architectures.

 * Familiarity with Kubernetes-based AI deployments, OpenAI-compatible APIs, and Python development
 * Experience in GPU inference optimization and working within NVIDIA GPU ecosystems

Nice to have:

 * Exposure to tools such as LangGraph, Semantic Kernel, vLLM, Ollama, Ray, and vector databases
 * Experience in integrating observability, cybersecurity, and scalable software delivery into AI platforms will help you succeed in supporting the continuous evolution and governance of enterprise AI systems

Eligibility requirements:

 * US Citizen
 * An active TS/SCI federal security clearance is required

## Description

* Design, develop, and operationalize AI and agentic AI systems for production mission environments
 * Implement and optimize AI/ML production engineering workflows, including LLMOps and MLOps best practices
 * Architect and deploy Retrieval-Augmented Generation (RAG) solutions and AI orchestration frameworks
 * Manage Kubernetes-based AI deployments and ensure seamless integration with OpenAI-compatible APIs
 * Develop and maintain Python-based AI applications, focusing on GPU inference optimization
 * Leverage tools and frameworks such as LangGraph, Semantic Kernel, vLLM, Ollama, and Ray for scalable AI solutions
 * Integrate with NVIDIA GPU ecosystems and vector databases to enhance AI performance and scalability
 * Collaborate with cross-functional teams in AI, DevSecOps, data engineering, platform engineering, and cybersecurity
 * Support enterprise AI governance, continuous monitoring, and observability for mission-critical applications
 * Contribute to the delivery of scalable, secure, and reliable AI software within a modern Hub-and-Spoke architecture
 * Participate in the integration of operational workflows to accelerate AI adoption and mission impact


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