About this role
At the American Cancer Society, we're working to end cancer as we know it, for everyone. Our employees and 1.3 million volunteers are raising the bar every single day. We are a culture comprised of diverse backgrounds and experience, to better serve our communities.
The people who work at the American Cancer Society focus their diverse talents on our lifesaving mission. It is a calling. And the people who answer it are fulfilled.
The Artificial Intelligence (AI) and Intelligent Automation (IA) Architect, Information Technology (IT), AI and Intelligent Automation serves as the Center of Excellences (CoE's) senior technical authority across all capability areas, Intelligent Document Processing (IDP), AI, and emerging technology. This role owns enterprise architecture standards, platform governance, delivery quality, and the technical roadmap for all automation and AI solutions at American Cancer Society (ACS). The Architect leads proof-of-concept (POC) efforts, mentors’ engineers and developers, and ensures all solutions are designed for scale, reuse, and governance compliance.
The AI and Intelligent Automation Architect defines and enforces CoE-wide architecture patterns and development standards across IDP, AI, and agentic capabilities. This role owns platform governance across all CoE tooling, leads the enterprise approach to Agentic AI and MCP Server infrastructure, architects RAG pipelines, governs API Gateway configuration, and manages IDP model training pipelines, serving as the single technical authority whose review gates every solution before production deployment.
We are looking for a deeply experienced, technically authoritative Architect who brings breadth across the full intelligent automation stack, from RPA bots and document intelligence to Large Language Model (LLM)-powered agentic systems. The AI and Intelligent Automation Architect partners with Information Security, IT Architecture, and business leadership to ensure that every CoE-delivered solution is secure, governed, and built for enterprise scale. This role reports to the Sr. Manager Delivery/Program.
***This is a fully remote position that can be home-based anywhere within the United States. Please be advised that selected candidate will be required to be onsite for the 1st day for onboarding activities.***
ESSENTIAL FUNCTIONS:
- Define and enforce CoE-wide architecture patterns, development standards, naming conventions, and reusable component libraries across RPA/RDA, IDP, AI, and agentic capabilities; conduct architecture and code reviews for all solutions prior to production deployment. 25%
- Lead the enterprise approach to Agentic AI, defining agent architecture patterns, orchestration frameworks, and safety guardrails; design and maintain the MCP Server ecosystem, define A2A communication standards, and govern API Gateway configuration for all AI and automation integrations. 25%
- Architect RAG pipelines connecting enterprise knowledge sources to LLM-powered applications; define IDP architecture patterns including document profiling, model training pipelines, human-in-the-loop workflows, and downstream integration standards. 20%
- Own platform governance across all CoE tooling, Orchestrator/Control Room, IDP platforms, AI services, and MCP Server infrastructure; evaluate and recommend platforms, models, and protocols and advise leadership on adoption readiness. 15%
- Maintain the CoE component and accelerator library, curating reusable automation, IDP, and AI components; mentor engineers, developers, and data scientists and drive continuous improvement in team technical capability. 10%
- Partner with Information Security and IT Architecture to ensure all solutions meet enterprise security, privacy, and governance standards; manage supervised learning pipelines for IDP model training including ground truth curation and model retraining. 5%
EXPERIENCE/QUALIFICATIONS:
- Minimum Degree Required: Bachelor's Degree in Computer Science, Information Technology, Software Engineering, or a related field (or equivalent work experience).
- Preferred Degree: Master's Degree in Computer Science, Artificial Intelligence, Systems Architecture, or a related technical field.
- Certificate( s ) or License( s ): Advanced certification in UiPath, Automation Anywhere, or Blue Prism required; Microsoft Azure Solutions Architect, AWS Solutions Architect, or equivalent enterprise architecture certification preferred.
- Years of Experience: Minimum of 10 years in Intelligent Automation, AI, or enterprise architecture, with at least 3 years in a lead architect or practice lead capacity.
- Advanced expertise across automation platforms (UiPath, Automation Anywhere, Blue Prism) and IDP platforms (ABBYY FlexiCapture, Azure AI Document Intelligence, UiPath Document Understanding, and Rossum).
- Deep expertise in LLM integration, prompt engineering, agentic AI system design, and generative AI application development; experience building multi-agent orchestration systems, MCP Server integrations, and A2A protocol implementations.
- Proficiency with vector databases (Pinecone, Weaviate, Azure AI Search), embedding models, RAG pipeline design, and API Gateway platforms (Azure API Management, AWS API Gateway, Kong).
- Knowledge of AI agent frameworks (LangChain, AutoGen, Semantic Kernel) and AI governance frameworks (NIST AI RMF, ISO 42001); familiarity with AI & Privacy Impact Assessment methodology.
KNOWLEDGE, SKILLS, AND ABILITY:
- Expert-level command of RPA platform architecture, UiPath (Studio, Orchestrator, REFramework), Automation Anywhere (A360), Blue Prism, and Microsoft Power Automate, including enterprise deployment patterns, credential management, and bot lifecycle governance.
- Deep expertise in IDP platform architecture, ABBYY FlexiCapture, Azure AI Document Intelligence, UiPath Document Understanding, including Optical Character Recognition ( OCR ) engine configuration, document classification model design, supervised learning pipelines, and human-in-the-loop review workflows.
- Deep expertise in LLM integration, prompt engineering, and generative AI application development; proven experience architecting agentic AI systems with multi-step reasoning, tool use, and memory management.
- Hands-on experience designing and building MCP Server ecosystems and A2A protocol implementations for multi-agent enterprise architectures.
- Proficiency with RAG pipeline architecture, document ingestion, chunking, embedding, vector storage (Pinecone, Weaviate, Azure AI Search), and retrieval optimization, and API Gateway governance (Azure API Management, AWS API Gateway, Kong).
- Ability to define and enforce enterprise-wide architecture patterns, development standards, naming conventions, and reusable component libraries across the full automation and AI capability stack.
- Experience conducting architecture and code reviews that enforce quality gates, testability standards, and production readiness criteria across multiple concurrent delivery teams.
- Knowledge of AI governance frameworks (NIST AI RMF, ISO 42001) and ability to partner on AI & Privacy Impact Assessments, risk scoring, and enterprise security reviews for all new AI and automation deployments.
- Demonstrated ability to mentor and develop engineers, developers, and data scientists; drive continuous improvement in team technical capability and CoE delivery standards.
- Strong executive communication skills; ability to advise senior leadership on platform adoption, technology strategy, and emerging AI and automation capabilities.
- Strong analytical and systems-thinking skills; ability to evaluate trade-offs across platforms, frameworks, and architectural approaches and produce clear architecture decision records.
TRAVEL REQUIREMENTS:
- Minimal travel- 0-10% - may be required for department or project meetings, vendor engagements, or team collaboration.
PHYSICAL REQUIREMENTS:
- Availability and ability to work after hours, weekends, holidays, etc. as needed, to be on call and/or to fulfill job responsibilities and requirements.
The starting rate is $114,000 to $144,000 annual. The final candidate's relevant experience/skills will be considered before an offer is extended. Actual starting pay will vary based on non-discriminatory factors including, but not limited to, geographic location, experience, skills, specialty, and education.
ACS provides staff a generous paid time off policy; medical, dental, retirement benefits, wellness programs, and professional development programs to enhance staff skills. Further details on our benefits can be found on our careers site at: jobs.cancer.org/benefits. We are a proud equal opportunity employer.