智能解决方案工程师负责人 - 远程美国
Lead Intelligent Solutions Engineer - Remote US
这不仅仅是一份职业,更是一项使命。
我们的员工是成功的基础。加入位于麦肯锡旗下萨拉·坎农研究所(SCRI)不断壮大的团队,你将有机会成为全球最大的基于社区的癌症项目之一,推动肿瘤治疗的发展,改善全球癌症患者的结果。我们寻找有使命感的候选人,他们渴望推进对抗癌症的斗争,并每天为被诊断出癌症的患者带来改变。
我们的使命
与癌症共处的人——那些努力预防、对抗和战胜癌症的人——是我们每个决策的核心。我们将最具创新力的医学人才与最富有热情的社区护理者汇聚在一起,正在改变医疗方式并实现个性化治疗。通过临床卓越和前沿研究,SCRI正在重新定义全球的癌症护理。
智能解决方案首席工程师是一个高级的、亲自参与的技术构建者-领导者,负责从问题定义到生产部署及持续价值实现的AI和智能自动化解决方案的端到端交付。该职位亲自设计、构建和扩展基于大语言模型(LLM)和代理的自动化方案,同时负责解决方案架构、技术质量、交付成果和企业标准。
该职位需要深厚的技术专业知识、强大的架构判断力,以及独立完成复杂、模糊项目的的能力。该职位不仅仅是监督;它专注于使用大型语言模型、代理、编排框架和企业集成进行定制AI开发、智能自动化和解决方案执行。
此外,该职位还期望在业务中推广并参与,将机会和问题转化为可信赖、可生产的AI解决方案,从而显著提高生产力、质量、周期时间和决策能力。
这是一个位于美国的远程职位。不提供搬迁补助和签证担保
职责包括但不限于:
亲自参与AI与智能自动化开发(主要责任)
- 独立设计、构建和维护:
- AI提示和提示库
- 基于LLM的代理和副驾驶
- 聊天机器人、自动化脚本和端到端智能工作流程
- 领导快速原型设计和实验;将成功案例转化为实际应用
查看英文原文
It’s More Than a Career, It’s a Mission.
Our people are the foundation of our success. By joining our growing team at Sarah Cannon Research Institute (SCRI), a subsidiary of McKesson, you will have the opportunity to become part of one of the largest community-based cancer programs to advance oncology treatments and improve outcomes for cancer patients across the globe. We look for mission-driven candidates who have a desire to advance the fight against cancer and make a difference in the lives of patients diagnosed with cancer every day.
Our Mission
People who live with cancer – those who work to prevent it, fight it, and survive it – are at the heart of every decision we make. Bringing the most innovative medical minds together with the most passionate caregivers in their communities, we are transforming care and personalizing treatment. Through clinical excellence and cutting-edge research, SCRI is redefining cancer care around the world.
The Lead Intelligent Solutions Engineer is a senior, hands‑on technical builder‑leader accountable for delivering AI and intelligent automation solutions end‑to‑end, from problem framing through production deployment and sustained value realization. This role personally designs, builds, and scales LLM‑ and agent‑based automations while owning solution architecture, technical quality, delivery outcomes, and enterprise standards.
This position requires deep technical expertise, strong architectural judgment, and the ability to independently drive complex, ambiguous initiatives to completion. The role is not oversight‑only; it is focused on custom AI development, intelligent automation, and solution execution using large language models, agents, orchestration frameworks, and enterprise integrations.
In addition, this role is expected to evangelize and engage the business, translating opportunities and problems into tangible, trusted, production‑ready AI solutions that measurably improve productivity, quality, cycle time, and decision‑making across SCRI.
This is a remote position based in the United States. Relocation assistance and visa sponsorship are not available
Duties include but are not limited to:
Hands‑On AI & Intelligent Automation Development (Primary Accountability)
- 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
End‑to‑End Solution Architecture & Delivery Ownership
- 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
Use Case Execution & Enterprise Impact
- 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
Governance, Security & Compliance (Lead‑Level Accountability)
- 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
Evangelism, Enablement & Technical Leadership
- 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
Minimum Qualifications:
- Bachelor's Degree required, Master's Degree preferred
- At least 7 years of experience in machine learning
Preferred Qualifications:
- Healthcare, life sciences, or clinical research domain experience
- Experience delivering solutions in regulated, compliance‑driven environments
Skills:
- 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 Python and/or JavaScript) with experience in APIs, data transformation, version control, and deployment practices
- Demonstrated experience building agentic AI solutions, including RAG architectures, orchestration frameworks, and tool‑calling patterns
- Experience with Microsoft AI ecosystem tools (e.g., Copilot Studio, Power Platform, Azure AI / Azure OpenAI) strongly preferred
- 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
- Comfortable owning ambiguous, high‑visibility initiatives with minimal direction
- Strong stakeholder influence skills; able to align technical decisions with business outcomes in a matrixed environment
- Track record of translating concepts into shipped, adopted, enterprise solutions
Abilities:
- 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.
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About Sarah Cannon Research Institute
Sarah Cannon Research Institute (SCRI) is one of the world’s leading oncology research organizations conducting community-based clinical trials. Focused on advancing therapies for patients over the last three decades, SCRI is a leader in drug development. In 2022, SCRI formed a joint venture with former US Oncology Research to expand clinical trial access across the country. It has conducted more than 850 first-in-human clinical trials since its inception and contributed to pivotal research that has led to the majority of new cancer therapies approved by the FDA in the past decade. SCRI’s research network brings together more than 1,300 physicians who are enrolling patients into clinical trials at more than 200 locations in 20+ states across the U.S. Please click here to learn more about our research offerings.
We care about the well-being of the patients and communities we serve, and that starts with caring for our people. That’s why we have a Total Rewards package that includes comprehensive benefits to support physical, mental, and financial well-being. Our Total Rewards offerings serve the different needs of our diverse colleague population and ensure they are the healthiest versions of themselves. For more information regarding benefits through our parent company, McKesson, please click here.
As part of Total Rewards, we are proud to offer a competitive compensation package. This is determined by several factors, including performance, experience and skills, equity, regular job market evaluations, and geographical markets. In addition to base pay, other compensation, such as an annual bonus or long-term incentive opportunities may be offered.
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McKesson Talent Advisors will never solicit money or credit card information in connection with a McKesson job application.
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We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
Originally posted on Himalayas