Lead Intelligent Solutions Engineer -...

Sarah Cannon Research Institute (SCRI) is hiring a Lead Intelligent Solutions Engineer to design, build, and deploy production-ready AI and intelligent automation solutions. The role owns solution architecture, delivery, governance, and ongoing technical health while partnering with business stakeholders to drive adoption and measurable enterprise impact.

Responsibilities:

• Independently design, build, and maintain: AI prompts and prompt libraries; LLM based agents and copilots; Chatbots, automation scripts, and end to end intelligent workflows
• Lead rapid prototyping and experimentation; convert successful pilots into scalable, production grade solutions
• Own the day-to-day technical health of deployed solutions, including monitoring, troubleshooting, performance tuning, and reliability improvements
• Build and maintain robust integrations with enterprise platforms using APIs, services, data pipelines, and workflow orchestration tools
• Serve as the end-to-end AI solution architect for assigned initiatives, making architectural decisions and implementing them hands on
• Define and standardize solution patterns for: Agent architectures (RAG, tool calling, multi agent orchestration); Integration and data flow design; Environmental promotion and deployment strategies (dev/test/prod)
• Own delivery planning with clearly defined value metrics, success criteria, and timelines
• Proactively identify technical risks, trade offs, and dependencies and drive resolution
• Lead execution for high-impact, enterprise-level AI and automation use cases, particularly complex or manual processes with measurable value potential
• Translate loosely defined business problems into durable, production-ready AI solutions
• Typical use cases include, but are not limited to: LLM-based agents for case intake, triage, summarization, and decision support; Intelligent document processing across emails, PDFs, forms, and unstructured content; Workflow automation for finance, operations, compliance, research, or shared services; Embedded AI assistants integrated into enterprise systems to reduce manual effort, errors, and cycle time
• Partner closely with business owners to validate outputs, refine logic, and ensure solutions are adopted, trusted, and operationalized
• Ensure all solutions comply with enterprise AI governance standards, ethical AI principles, and corporate policies
• Design and implement secure-by-default solutions, including documentation, traceability, monitoring, and audit readiness
• Anticipate and mitigate risks related to data privacy, access control, model behavior, hallucinations, bias, and operational resilience
• Partner with architecture, security, and data governance teams to ensure compliant solution design, especially within regulated environments
• Evangelize AI and intelligent automation capabilities across the organization by: Engaging business stakeholders; Translating opportunities into concrete solution concepts; Demonstrating value through working solutions
• Produce high-quality technical documentation, user guides, and SOPs
• Lead hands-on enablement sessions, workshops, and knowledge transfer to drive adoption
• Act as a technical mentor and thought leader, influencing standards, patterns, and best practices across AI and automation initiatives
• Collaborate with business and technology partners to continuously improve AI-enhanced workflows