AI / ML Engineer

The posting, as Accenture Federal Services wrote it

At Accenture Federal Services, nothing matters more than helping the US federal government make the nation stronger and safer and life better for people. Our 13,000+ people are united in a shared purpose to pursue the limitless potential of technology and ingenuity for clients across defense, national security, public safety, civilian, and military health organizations.

Join Accenture Federal Services, a technology company within global Accenture. Recognized as a Glassdoor Top 100 Best Place to Work, we offer a collaborative and caring community where you feel like you belong and are empowered to grow, learn and thrive through hands-on experience, certifications, industry training and more.

Join us to drive positive, lasting change that moves missions and the government forward!

We are seeking an AI Enginee r with strong experience in Large Language Models (LLMs) and Retrieval‑Augmented Generation (RAG) to design, build, and optimize intelligent systems that solve complex mission and enterprise challenges. This role blends modern GenAI engineering with traditional computer science and machine learning, supporting both rapid prototyping and production‑grade delivery.

Responsibilities

• Design, develop, and maintain RAG pipelines, including document ingestion, embedding generation, vector storage, retrieval logic, and LLM orchestration.
• Build and optimize LLM‑powered applications for classification, summarization, Q&A, knowledge retrieval, and workflow automation.
• Apply core software engineering and ML fundamentals to ensure performance, reliability, and security (e.g., data structures, algorithms, model evaluation, MLOps, API development).
• Implement and tune traditional ML models when required (e.g., regression, clustering, feature engineering, classical NLP).
• Integrate cloud‑native services (Azure/AWS), data pipelines, and containerized workloads (Docker). Collaborate closely with cross‑functional teams—including data engineers, architects, and mission SMEs—to translate requirements into scalable solutions.

Qualifications

• Hands‑on experience with LLMs, prompt engineering, embeddings, vector databases, and RAG frameworks.
• Strong programming skills in Python; familiarity with Java/C++ is a plus. Proficiency with ML and DL frameworks (PyTorch, TensorFlow, HuggingFace).
• Solid understanding of algorithms, data structures, APIs, and distributed systems. Experience with cloud platforms (AWS or Azure) and containerization (Docker). Ability to work across structured and unstructured datasets.

Preferred Skills

• Experience building production‑ready AI/ML systems, including CI/CD or MLOps frameworks (MLFlow/BentoML).
• Understanding of data governance, security constraints, and model risk management.
• Ability to communicate complex technical concepts to non‑technical stakeholders.

Clearance

• An active TS/SCI is required

As required by local law, Accenture Federal Services provides reasonable ranges of compensation fo
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ions of your role, you will be asked to participate in our reasonable accommodation process. Accommodations made to facilitate the recruiting process are not a guarantee of future or continued accommodations once hired.

If you are being considered for employment opportunities with Accenture Federal Services and need an accommodation for a disability or religious observance during the interview process or for the job you are interviewing for, please speak with your recruiter.

Other Employment Statements

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.

Candidates who are currently employed by a client of Accenture Federal Services or an affiliated Accenture business may not be eligible for consideration.

Job candidates will not be obligated to disclose sealed or expunged records of conviction or arrest as part of the hiring process.

The Company will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. Additionally, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by the employer, or (c) consistent with the Company's legal duty to furnish information.

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