Quick overview
Job description
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.
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 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.
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