Design and develop artificial intelligence AI and machine learning ML systems leveraging existing cloud AI services. Design and build scalable data pipelines to support model training and production with DevOps MLOps. Customize and apply Deep Learning and Gen AI models for use cases based on the business needs, data availability, system and infrastructure requirements including edge devices and High Performance Computers HPCs . Justify the quality and value of the solution. Engage in research and development of new AI and high performance compute algorithms, models, and simulations along with their applications to solve complex problems. Work with large scale datasets and utilize data preprocessing techniques to ensure high quality input for training and production. Implement and maintain efficient data storage and retrieval mechanisms for models and knowledge using appropriate tools.
What you need:
3+ years of experience designing and implementing agentic AI architectures and multi-agent systems using LLMs.
3+ years of hands-on experience with Azure OpenAI, AWS Bedrock (Claude), and cloud-based AI services.
2+ years of proven expertise building RAG (Retrieval Augmented Generation) systems using vector databases such as Redis, Pinecone, or Azure AI Search.
3+ years of experience leading AI/ML projects from PoC through production deployment.
3+ years of proficiency in Python with deep learning frameworks (PyTorch, Keras) and NLP libraries (NLTK, Spacy).
2+ years of experience translating business processes into AI solution architectures and agent workflows.
2+ years of experience deploying and scaling agentic AI solutions in enterprise production environments.
Bonus points if you have experience with:
Proven ability to leverage state-of-the-art AI coding agents (e.g., GitHub Copilot, Cursor, Claude Code) to accelerate development velocity.
Strong knowledge of prompt engineering best practices and prompt flow orchestration.
Hands-on experience with popular open source agentic AI frameworks such as LangChain and LangGraph.
Ability to lead cross-functional workshops to identify business needs and develop AI-driven solutions.
Experience building agent orchestration frameworks with tool-use, memory, and autonomous decision-making capabilities.
Track record of shipping multi-agent systems that handle real-world enterprise workflows at scale.
Compensation at Accenture varies depending on a wide array of factors, which may include but are not limited to the specific office location, role, skill set, and level of experience. As required by local law, Accenture provides a reasonable range of compensation for roles that may be hired as set forth below.
We anticipate this job posting will be posted until 05/14/2026.
Accenture offers a market competitive suite of benefits including medical, dental, vision, life, and long-term disability coverage, a 401(k) plan, bonus opportunities, paid holidays, and paid time off. See more information on our benefits here:
U.S. Employee Benefits | Accenture
Role Location Annual Salary Range
California $94,400 to $293,800
Cleveland $87,400 to $235,000
Colorado $94,400 to $253,800
District of Columbia $100,500 to $270,300
Illinois $87,400 to $253,800
Maryland $94,400 to $253,800
Massachusetts $94,400 to $270,300
Minnesota $94,400 to $253,800
New York $87,400 to $293,800
New Jersey $100,500 to $293,800
Washington $100,500 to $270,300
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