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Accenture

Advises businesses and runs their technology

Industry & Functions AI Decision Science Manager

Natural Language Processing & LLMsPosted on Nov 12
Full-timeNo salary listed

About the Job

Requirements

  • Expert proficiency in Generative AI, agentic AI systems, Model Context Protocol (MCP), Large Language Models (LLMs), multi-agent systems, Python, SQL, and AI agent orchestration frameworks.
  • Knowledge of cloud platforms including AWS, Azure, or GCP; Docker; Kubernetes; Spark; and MLOps pipelines for agentic systems.
  • Specialized knowledge of natural language processing (NLP), computer vision, reinforcement learning for agent training, and multimodal AI systems.
  • Experience developing AI and machine-learning models.
  • Deep expertise in agentic AI systems and a proven track record of building autonomous AI solutions that execute complex business workflows.
  • Strong understanding of AI safety, alignment, and governance principles for autonomous systems.
  • Experience with enterprise-grade AI agent deployments and production system management.

Responsibilities

  • Oversee the end-to-end lifecycle of AI projects, from requirements gathering and solution architecture to deployment and post-implementation support.
  • Provide thought leadership and guidance to consultants and engineers on generative AI and agentic AI technologies.
  • Define and communicate a strategic vision for AI agent solutions, ensuring alignment with client business objectives.
  • Act as a trusted advisor to clients, translating complex AI concepts into actionable business solutions.
  • Drive discussions on generative AI best practices, risk management, AI safety, and governance.
  • Design and implement AI agents using frameworks such as AI Refinery, LangChain, AutoGen, CrewAI, and custom agentic architectures.
  • Develop multi-agent systems that collaborate, negotiate, and execute complex workflows autonomously.
  • Implement Model Context Protocol integrations for communication between AI systems and external tools and APIs.
  • Build and deploy generative AI applications with advanced reasoning, planning, and execution capabilities.
  • Develop solutions using computer vision, machine learning, and large language models.
  • Define data requirements; clean, aggregate, analyze, and interpret data; and conduct data quality assessments.
  • Build and deploy AI models and generative AI applications.
  • Train and fine-tune large language models using large-scale datasets to optimize performance and accuracy.
  • Evaluate model performance and implement iterative improvements.
  • Collaborate to integrate AI solutions into end-to-end workflows and ensure scalability.
  • Use cloud platforms such as AWS, Azure, or GCP for model development and deployment.
  • Stay current with advancements in AI and data science and explore innovative techniques and frameworks.
  • Document methodologies and findings for knowledge sharing.

Desired Qualifications

  • AI Refinery, LangChain, LlamaIndex, AutoGen, CrewAI, Spark, AWS, Azure, GCP, NLP, computer vision, vector databases, retrieval-augmented generation (RAG), function calling, and tool integration.

About the Company

Accenture

Advises businesses and runs their technology

Accenture advises large businesses and public agencies on strategy, builds their technology systems and runs ongoing operations. Its teams connect business planning with implementation, covering areas such as cloud migration, cybersecurity and customer experience. Consultants work with clients to redesign processes, while engineers integrate software from technology partners and maintain the resulting systems for multinational organizations. Clients pay for project work or continuing services, including application support and business processes such as finance and customer service. Accenture was founded in 1989 and has its headquarters in Dublin, Ireland.

Company size
10,001+
Company stage
IPO
Headquarters
Dublin, Ireland
Founded
1989

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