Advanced AI Applications Senior Manager

Accenture•Miami, FL

3d•$112,900 - $338,300•Hybrid

About The Position

Accenture is stepping boldly into a new Data & AI decade, aiming to help clients optimize and reinvent their businesses with data & AI. With a $3B investment and a commitment to its people, Accenture's Data & AI organization brings together experienced innovation, strategic investment, exceptional talent, and a powerful ecosystem. This role seeks a highly skilled Advanced AI Applications Consultant to drive the integration of Artificial Intelligence across the enterprise digital core. The ideal candidate will possess expertise spanning classical AI/ML, Generative AI, Agentic AI, and enterprise-scale AI platforms, with strong hands-on experience across the Anthropic Claude and OpenAI ecosystems. This role requires a unique blend of strategic consulting, solution architecture, and technical implementation capabilities to design, build, and scale intelligent business applications leveraging modern AI technologies across cloud platforms including Azure, AWS, and Google Cloud. The consultant will help clients transform core business processes by embedding AI into enterprise applications, data platforms, business workflows, and decision-making systems while ensuring scalability, governance, security, and measurable business outcomes.

Requirements

Minimum of 8 years of experience in AI, Machine Learning, Data Science, AI Engineering, or AI Consulting with proven experience delivering enterprise AI transformation initiatives.
Minimum of 5 years of hands-on experience with Anthropic Claude Models, OpenAI GPT Models, Large Language Models (LLMs), Foundation Models, Agentic AI Frameworks, Multi-Agent Architectures, Retrieval-Augmented Generation (RAG), LLM Evaluation Frameworks with deep understanding of prompt engineering, context engineering, and AI reasoning strategies.
Bachelor's degree or equivalent (minimum 12 years) work experience. (If Associate Degree, must have minimum 6 years work experience).
Experience building production-grade AI applications and intelligent automation solutions.
Strong consulting and stakeholder management capabilities.
Strong programming experience in: Python, SQL, APIs and Integration Frameworks.
Experience with: Vector Databases, Embedding Models, Semantic Search Platforms, Data Engineering Pipelines, Cloud-Native Architectures.
Knowledge of AI orchestration and workflow frameworks.

Nice To Haves

Travel may be required for this role. The amount of travel will vary from 0 to 100% depending on business need and client requirements.

Responsibilities

Design and implement enterprise AI solutions leveraging both classical machine learning and advanced AI architectures.
Build AI-powered applications for Customer Service, and enterprise functions like Supply Chain, Finance, Procurement, HR, Operations, IT Service Management, Enterprise Knowledge Management.
Develop Retrieval-Augmented Generation (RAG) and Agentic AI solutions integrated with enterprise systems.
Design intelligent workflows using AI agents capable of reasoning, planning, and executing business tasks.
Establish reusable AI accelerators following "Build Once, Scale Many Times" principles.
Design and implement Agentic AI architectures capable of Goal-based reasoning, Planning and orchestration, Tool utilization, Workflow automation, Multi-agent collaboration.
Build AI agents integrated with enterprise systems, APIs, and business applications.
Implement autonomous business workflows using AI orchestration frameworks.
Establish agent governance, observability, and human-in-the-loop controls.
Develop and deploy machine learning solutions including Predictive Analytics, Classification Models, Forecasting Models, Recommendation Engines, Optimization Models, NLP Applications.
Perform feature engineering, model tuning, evaluation, and deployment.
Implement end-to-end ML lifecycle management.
Design and implement RAG Architectures, Enterprise Chatbots, AI Copilots, Knowledge Assistants, Document Intelligence Solutions, Content Generation Platforms.
Optimize prompt engineering and context management strategies.
Develop AI evaluation and benchmarking frameworks.
Build autonomous AI agents capable of Tool Calling, Workflow Orchestration, Multi-step Reasoning, Dynamic Decision Making, Enterprise System Integration.
Design multi-agent collaboration frameworks and intelligent task delegation architectures.
Design enterprise knowledge systems using Vector Databases, Knowledge Graphs, Semantic Search, Embedding Models, Context Management Frameworks.
Build enterprise memory architectures supporting long-term AI interactions.