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Sarah Cannon Research Institute

Community-based oncology clinical research organization

Lead Intelligent Solutions Engineer

AI Application EngineeringPosted on Nov 11
Full-timeRemote in USA

About the Job

Requirements

  • A bachelor's degree is required.
  • At least 7 years of experience in machine learning is required.
  • Proven experience delivering complex, production-grade AI and automation solutions as a hands-on builder.
  • Deep proficiency in prompt engineering and applying generative AI to enterprise workflows.
  • Strong programming skills, typically in Python and/or JavaScript, with experience in APIs, data transformation, version control, and deployment practices.
  • Demonstrated experience building agentic AI solutions, including retrieval-augmented generation architectures, orchestration frameworks, and tool-calling patterns.
  • Ability to rapidly prototype while maintaining enterprise-grade security, reliability, and governance.
  • Demonstrated ability to operate as a senior, end-to-end AI solution architect while remaining hands-on.
  • Ability to own ambiguous, high-visibility initiatives with minimal direction.
  • Ability to align technical decisions with business outcomes in a matrixed environment.
  • Track record of translating concepts into shipped, adopted enterprise solutions.
  • Ability to operate simultaneously at strategic, architectural, and engineering levels.
  • Ability to influence change and drive adoption across teams.
  • Ability to prioritize, execute, and deliver outcomes under evolving requirements.

Responsibilities

  • Independently design, build, and maintain AI prompts and prompt libraries; large language model-based agents and copilots; chatbots, automation scripts, and end-to-end intelligent workflows.
  • Lead rapid prototyping and experimentation, and 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, including retrieval-augmented generation, tool calling, and multi-agent orchestration; integration and data-flow design; and development, test, and production promotion and deployment strategies.
  • Own delivery planning with clearly defined value metrics, success criteria, and timelines.
  • Identify technical risks, trade-offs, and dependencies and drive their 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.
  • Develop large language model-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; and embedded AI assistants integrated into enterprise systems to reduce manual effort, errors, and cycle time.
  • Partner 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 by engaging business stakeholders, translating opportunities into concrete solution concepts, and demonstrating value through working solutions.
  • Produce high-quality technical documentation, user guides, and standard operating procedures.
  • 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.

Desired Qualifications

  • A master's degree is preferred.
  • Healthcare, life sciences, or clinical research domain experience.
  • Experience delivering solutions in regulated, compliance-driven environments.
  • Experience with Microsoft AI ecosystem tools such as Copilot Studio, Power Platform, Azure AI, or Azure OpenAI.

About the Company

Sarah Cannon Research Institute

Community-based oncology clinical research organization

Sarah Cannon Research Institute (SCRI) is a global oncology research organization that conducts cancer clinical trials in community settings, partnering with pharmaceutical and biotech sponsors, physicians, and patients to develop new treatments. It works as an oncology-focused contract research organization (CRO) and centralized site management organization (SMO), running trials across more than 200 locations with roughly 1,500 research physicians, and applies technology such as its Accelero platform to personalized-medicine studies. Over more than 30 years it has completed more than 900 first-in-human trials across early- to late-phase research. What sets SCRI apart is this community-based model paired with early-phase depth, which has helped advance most new cancer therapies the FDA approved in the past decade. The goal is to accelerate oncology research from early trials to approval and bring advanced cancer treatments to patients.

Company size
1-10
Company stage
Not listed
Total funding
Not listed
Headquarters
Beach Haven, NJ
Founded
Not listed

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