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Accenture

Advises businesses and runs their technology

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, multi-agent systems, Python, SQL, and AI agent orchestration frameworks.
  • Experience developing AI and machine-learning models.
  • Experience with cloud platforms such as AWS, Azure, or GCP; Docker; Kubernetes; Spark; and MLOps pipelines for agentic systems.
  • Knowledge of natural language processing, computer vision, reinforcement learning for agent training, and multimodal AI systems.
  • Deep expertise in agentic AI systems and a proven track record 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 AI project lifecycles from requirements gathering and solution architecture through 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 aligned with client business objectives.
  • Advise clients and translate complex AI concepts into actionable business solutions.
  • Lead 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 to enable communication between AI systems and external tools and APIs.
  • Build and deploy generative AI applications with 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 datasets, evaluate their performance, and iteratively improve them.
  • 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.
  • Explore advances in AI and data science, and document methodologies and findings for knowledge sharing.

Desired Qualifications

  • AI Refinery, LangChain, LlamaIndex, AutoGen, CrewAI, Spark, cloud platforms (AWS, Azure, or GCP), natural language processing, 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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