We are seeking a highly skilled AI Engineer Subject Matter Expert (SME) to support mission-critical programs within the federal and national security community. In this role, you will lead the design, development, and deployment of advanced Artificial Intelligence (AI), Machine Learning (ML), and Generative AI (GenAI) solutions that drive operational impact and innovation across
The Work:
- Architect, develop, and deploy enterprise-scale AI, ML, and Generative AI solutions supporting mission objectives.
- Design and maintain robust data pipelines to support model training, evaluation, deployment, and inference.
- Develop advanced AI/ML applications using Python and industry-leading frameworks.
- Operationalize machine learning models through MLOps best practices, CI/CD pipelines, and containerized deployment strategies.
- Design, develop, and maintain APIs, microservices, and scalable AI services.
- Optimize AI models for accuracy, performance, latency, reliability, and scalability.Integrate Large Language Models (LLMs), embeddings, retrieval-augmented generation (RAG) architectures, and vector database technologies.
- Collaborate with cross-functional stakeholders to translate mission requirements into technical solutions.
- Ensure adherence to AI governance, security, compliance, and responsible AI standards.
- Provide technical leadership, engineering guidance, and subject matter expertise across AI initiatives.
Here is what you'll need:
- Bachelor's degree in Computer Science, Engineering, Data Science, Mathematics, or a related technical field. Additional relevant experience may be considered in lieu of a degree.
- 10+ years of experience designing, building, and deploying AI/ML solutions in production environments.
- Expert-level Python development experience.
- Deep understanding of algorithms, data structures, distributed computing, and software engineering principles.
- Hands-on experience deploying and supporting production Generative AI and LLM-based solutions.
- Experience with embeddings, vector databases, RAG architectures, prompt engineering, and AI orchestration frameworks.
- Strong proficiency with machine learning frameworks such as PyTorch, TensorFlow, and Scikit-learn.
- Experience deploying solutions within cloud environments including AWS, Azure, or Google Cloud Platform.
- Experience implementing MLOps practices and tools such as MLflow, Azure Machine Learning, Vertex AI, or similar platforms.
- Experience developing scalable APIs, microservices, and containerized applications using Docker and Kubernetes.
Bonus points you might have:
- Experience supporting Federal Civilian, Defense, Intelligence Community, or other highly regulated government environments.
- Knowledge of Responsible AI, AI governance frameworks, and model risk management practices.
- Experience with large-scale distributed training, GPU acceleration, and high-performance computing environments.
- Background in Natural Language Processing (NLP), Computer Vision, Reinforcement Learning, or Agentic AI architectures.
- Experience designing and implementing secure AI solutions within classified environments.
Eligibility Requirements:
- US Citizenship with an at least Active Top Secret Clearance.
As required by local law, Accenture Federal Services provides reasonable ranges of compensation for hired roles based on labor costs in the states of California, Colorado, Connecticut, Hawaii, Illinois, Maine, Maryland, Massachusetts, Minnesota, New Jersey, New York, Ohio, Vermont, Virginia, Washington, and the District of Columbia. The base pay range for this position in these locations is shown below. Compensation for roles at Accenture Federal Services varies depending on a wide array of factors, including but not limited to office location, role, skill set, and level of experience. Accenture Federal Services offers a wide variety of benefits. You can find more information on benefits here. We accept applications on an on-going basis and there is no fixed deadline to apply.