About this role
Designing and building retrieval-augmented generation pipelines, developing applications for document summarization and classification, and tuning machine learning models occupy the daily schedule for this position. Accenture Federal Services builds intelligent systems to address complex challenges for US federal government agencies across defense, civilian, and military health organizations. Engineers in this group handle tasks ranging from rapid prototyping to production-grade delivery while collaborating closely with data engineers, architects, and mission subject matter experts.
The team focuses on modern generative AI engineering combined with classical computer science fundamentals to support critical federal missions. Successful candidates bring hands-on expertise in large language models alongside solid programming skills in Python and familiarity with cloud-native environments. This position suits methodical engineers who want to apply technical ingenuity toward public service and national security goals within a collaborative team structure.
What you will do
- Design, develop, and maintain RAG pipelines that cover document ingestion, embedding generation, vector storage, retrieval logic, and LLM orchestration.
- Build and optimize LLM-powered applications dedicated to classification, summarization, Q&A, knowledge retrieval, and workflow automation.
- Apply core software engineering and machine learning fundamentals to guarantee performance, reliability, and security across distributed systems.
- Implement and tune traditional machine learning models including regression, clustering, feature engineering, and classical natural language processing.
- Integrate cloud-native services on Azure or AWS alongside data pipelines and containerized workloads using Docker.
- Collaborate directly with cross-functional teammates like data engineers, architects, and mission SMEs to translate requirements into scalable solutions.
What you need
- Possess hands-on experience working with LLMs, prompt engineering, embeddings, vector databases, and RAG frameworks.
- Demonstrate strong programming skills in Python alongside familiarity with Java or C++.
- Show proficiency using machine learning and deep learning frameworks such as PyTorch, TensorFlow, and HuggingFace.
- Maintain a solid understanding of algorithms, data structures, APIs, and distributed systems.
- Bring previous experience with cloud platforms like AWS or Azure and containerization tools like Docker.
- Manage and work effectively across both structured and unstructured datasets.
- Hold an active TS/SCI security clearance.
Nice to have
- Experience building production-ready AI and ML systems including CI/CD or MLOps frameworks like MLFlow or BentoML
- Understanding of data governance, security constraints, and model risk management
- Ability to communicate complex technical concepts to non-technical stakeholders
Skills and tech stack
Questions candidates ask
What is the salary range for the role?
The base pay range for this position in specific states such as California, Colorado, New York, and Virginia is $100,600 to $135,100 USD. Compensation varies depending on factors including office location, role, skill set, and level of experience.
What security clearance is required?
An active TS/SCI security clearance is required for this position. Candidates must meet this clearance requirement to be eligible for consideration.
What are the visa sponsorship requirements?
Applicants for employment in the US must have work authorization that does not now or in the future require sponsorship of a visa for employment authorization in the United States. Visa sponsorship is not provided for this role.
How does the application process work?
Applications are accepted on an ongoing basis with no fixed deadline to apply. Qualified candidates can submit their materials directly through the hiring portal.
The application is on the official Accenture Federal Services careers page.
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