Design and develop RAG pipelines and LLM-powered applications for federal government missions, building production-ready systems with Python, PyTorch, and cloud platforms like Azure or AWS. You'll handle document ingestion, vector storage, model optimization, and traditional ML implementation alongside modern GenAI engineering. Strong hands-on experience with LLMs, embeddings, and vector databases required; proficiency with Docker and distributed systems expected. Active TS/SCI clearance required. Salary $100,600–$135,100.
Written from this posting by Neural Jobs AI. The full description is below.
We are seeking an AI Engineer 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.
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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, Hawaii, Illinois, Maine, Maryland, Massachusetts, Minnesota, New Jersey, New York, Vermont, Virginia, Washington, and the District of Columbia, and the city of Cleveland. 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.
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