Advanced AI Applications Senior Manager

Accenture•Chicago, IL

1d•Hybrid

About The Position

We Are: The beginning of a new Data & AI decade that will reshape work and society has begun. Accenture is stepping boldly into this future with a clear strategy and purpose: to help clients optimize and reinvent their business with data & AI — backed by a $3B investment and commitment to our people to do industry-defining work. With over 45,000 professionals dedicated to Data & AI, Accenture’s Data & AI organization brings together our Experienced Innovation, Strategic Investment, Exceptional Talent, and Power Ecosystem. You are: 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.
Applicants for employment in the US must have work authorization that does not now or in the future require sponsorship of a visa for employment authorization in the United States.

Responsibilities

Advanced AI Applications & Solution Design: 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.
Agentic AI & Autonomous Systems: 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.
Technical Responsibilities: Classical AI / Machine Learning: 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.
Generative AI: 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.
Agentic AI: 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.
Knowledge & Semantic 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.