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# AI Engineer - Senior

- **Company:** Accenture
- **Location:** Chantilly, VA, United States
- **Experience:** Expert
- **Salary:** $94,000.0 - $187,600.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Computer Vision, Microsoft Azure, Computer Programming, Continuous Integration, Data Structures, Distributed Computing Environment, Distributed Systems, Python (Programming Language), Tensorflow, Azure Machine Learning, Secure Coding, Reinforcement Learning, Pytorch, Large Language Models, Generative AI, Containerization, Scikit Learn, Low Latency, Machine Learning Operations, Api Design, Data Pipelines, Microservices
- **Published:** October 16, 2026
- **Apply:** https://www.techcareers.com/job.asp?id=3451615243&tx=JL7973FFJ&pt=1&aff=0B19D771-A501-4A5E-8338-2A822B784D54&utm_source=Job%20Feed&utm_medium=textkernel&utm_campaign=DE&utm_term=0B19D771-A501-4A5E-8338-2A822B784D54

## About the Role

* US Citizen with an Active TS/SCI CIP
 * Bachelor's degree required with a minimum of 8 years of experience in AI/ML.
 * Advanced Python programming skills.
 * Strong understanding of algorithms, data structures, and distributed systems.
 * Hands-on experience with ML frameworks like PyTorch, TensorFlow, and scikit-learn.
 * Proficiency with cloud platforms such as AWS, Azure, or GCP.
 * Experience deploying production GenAI/LLM systems, embeddings, and vector databases.
 * Practical experience with MLOps tools such as MLflow, Azure ML, or Vertex AI.
 * Background in NLP, computer vision, or reinforcement learning., * Experience in federal, defense, or highly regulated environments.
 * Knowledge of ethical AI, governance frameworks, and secure development practices.
 * Skills in large-scale optimization, GPU acceleration, or distributed training.
 * Experience building APIs, microservices, and automated ML workflows.

## Description

We are seeking an experienced AI/ML Engineer to design, develop, and deploy scalable, production-ready AI systems. This role involves building data pipelines, implementing algorithms, and operationalizing models using MLOps. The ideal candidate will optimize models for accuracy, latency, and scalability, while ensuring compliance with AI governance and ethical standards.

What you'll do:

 * Design, develop, and deploy scalable AI, ML, and generative AI systems.
 * Build data pipelines for model training, evaluation, and inference.
 * Implement algorithms in Python and operationalize models using MLOps, CI/CD, and containerization frameworks.
 * Design and maintain APIs and microservices.
 * Optimize models for accuracy, latency, and scalability.
 * Ensure compliance with AI governance, documentation, and ethical standards.
 * Collaborate with agile engineering teams to deploy production-level GenAI models and applications.