AI Engineer - SME

Accenture Federal Services•Chantilly, VA

About The Position

Accenture Federal Services is seeking a seasoned AI/ML Engineer to design, develop, and deploy scalable, production-ready AI systems for U.S. federal government missions. The role includes building data pipelines, implementing algorithms in Python, operationalizing models using MLOps, CI/CD, and containerization, and optimizing models for performance. The engineer is also responsible for ensuring compliance with AI governance, documentation, and ethical standards. The position serves defense, national security, public safety, civilian, and military health organizations. Applicants must be U.S. citizens with an active TS/SCI CIP clearance and a bachelor's degree in a relevant field, along with 10 years of AI/ML engineering experience. The role is full-time; work location is not specified.

Requirements

U.S. citizenship and an active TS/SCI CIP clearance.
Bachelor's degree in a relevant field.
10 years of experience in AI/ML engineering.
Advanced Python programming skills.
Strong understanding of algorithms, data structures, and distributed systems.
Hands-on experience deploying production GenAI/LLM systems, embeddings, and vector databases.
Proficiency with ML frameworks such as PyTorch, TensorFlow, and scikit-learn.
Experience with cloud platforms such as AWS, Azure, or GCP.
Practical experience with MLOps tools such as MLflow, Azure ML, or Vertex AI.
Background in NLP, computer vision, or reinforcement learning.

Nice To Haves

Experience in federal, defense, or highly regulated environments.
Knowledge of ethical AI and governance frameworks.
Skills in large-scale optimization, GPU acceleration, or distributed training.
Experience building APIs, microservices, and automated ML workflows.

Responsibilities

Design, develop, and deploy AI, machine learning, and generative AI systems.
Build and maintain data pipelines for model training, evaluation, and inference.
Implement algorithms using languages such as Python.
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.