You AreA hands-on technologist with the range to operate across design, delivery, and client work within complex transformation programs. You understand how enterprise IT organizations work and bring the drive to translate that understanding into AI solutions that ship and deliver value.
The WorkAI is reshaping what enterprises can build, how fast they can move, and where competitive advantage comes from. Capturing that opportunity requires architecture that holds at estate scale, engineering that ships to production, and the leadership to connect both to measurable business outcomes.
As a Manager, you lead solution design and workstream delivery within transformation programs, develop client relationships, and own architecture decisions from design through to production:
- Design and architect AI solutions: Design multi-agent systems (planning, execution, evaluation, and coordination roles), LLM integrations, and RAG pipelines on vector databases (Qdrant, Pinecone, ChromaDB, Weaviate), and own those decisions through to production delivery. Build with LLM APIs (Claude/Anthropic, GPT-4), prompt engineering, and agentic frameworks (LangChain, LlamaIndex, or custom orchestration built for production). Design and implement MCP Server/Client. Judge where AI adds value in an enterprise context and where it does not.
- Own AI quality and observability: Apply LLM tracing, failure mode analysis, LLMOps, and prompt versioning. Run AI evaluation, quality assurance, risk assessment, and compliance for enterprise AI deployments.
- Design and enable the foundation for agentic transformation: Own solution-level architecture on technology or AI programs. Define integration patterns (microservices, event-driven design, API-led integration, with containerization and orchestration on Docker and Kubernetes and streaming on Kafka, Kinesis, or EventBridge where the solution needs them), data flows, and data foundations (knowledge graphs and graph databases such as Neo4j and Neptune, ontologies, data integration patterns, semantic layers). Fit the solution into major enterprise platforms (ERP, CRM, data platforms, cloud infrastructure), the core services and deployment patterns of AWS, Azure, and GCP, and the operating model structures that make AI adoption work in practice, not just on paper.
- Apply AI-assisted engineering: Use AI coding agents (Claude Code, GitHub Copilot, Cursor) and AI-augmented development workflows hands-on, and set how they change delivery speed and engineering governance.
- Advise and contribute to the business case: Translate client requirements into architecture decisions and communicate the reasoning, with solution design and architecture documentation. Contribute to ROI and efficiency estimation, token cost modeling, spend optimization, and business cases for AI investments, and show how cost structure shapes architecture choices.
- Lead workstream delivery: Own a delivery workstream end-to-end: scope, tasks, dependencies, risk management, and reporting to program leadership. Track delivery commitments, surface blockers early, and coordinate across team members.
- Develop client relationships: Build trusted relationships with senior manager and director-level client stakeholders. Communicate technical decisions clearly, structure problems into options and a recommendation, and bring technical insight and vertical awareness (financial services, healthcare, retail, logistics, or public sector).
- Support business development: Contribute to proposals, solution shaping, and presentations, and identify opportunities within existing engagements.
- Coach Architects and Consultants and build the practice: Provide day-to-day technical and professional guidance, document patterns, capture reusable learnings, and build assets that improve delivery quality across the team. Follow developments in AI, architecture, and enterprise technology and bring new thinking into delivery work.
Travel may be required for this role. The amount of travel will vary from 50 to 80% depending on business need and client requirements.
Here's what you need- Minimum of 5 years of experience in technology consulting, software engineering, or enterprise architecture.
- Minimum of 5 years of hands-on software development experience with production deployments.
- Minimum of 5 years of experience leading IT projects or a cross-functional team.
- Minimum of 1 year of experience building agentic or LLM-based systems (for example multi-agent orchestration, RAG pipelines, or LLM API integration) in production contexts.
- Minimum of 1 year of experience using AI coding agents (for example Claude Code, GitHub Copilot, or Cursor) in software development workflows.
- Familiarity with at least one vertical (financial services, healthcare, retail, logistics, or public sector), including how its business processes, technology stack, or regulatory environment shape AI adoption.
- Bachelor's degree or equivalent (minimum 12 years) work experience. (If Associate's Degree, must have minimum 6 years work experience)
Bonus Points if you Have- Graph databases and knowledge graphs (Neo4j, Neptune)
- Professional cloud certification (AWS, Azure, GCP) or AI/ML certification (AWS ML Specialty, GCP Professional ML Engineer, Azure AI Engineer)
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 11/30/2026.
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 $266,300
Colorado $94,400 to $230,000
Connecticut $94,400 to $230,000
District of Columbia $100,500 to $245,000
Illinois $87,400 to $230,000
Maine $80,400 to $196,000
Maryland $94,400 to $230,000
Massachusetts $94,400 to $245,000
Minnesota $94,400 to $230,000
New York $87,400 to $266,300
New Jersey $100,500 to $266,300
Ohio $87,400 to $213,000
Virginia $87,400 to $245,000
Washington $100,500 to $245,000
