Lead Intelligent Solutions Engineer - Remote US

Role overview

A senior, hands-on builder-leader role accountable for delivering AI and intelligent automation solutions end-to-end, from problem framing through production deployment and sustained value realization. The position combines custom AI development, intelligent automation, and solution execution using large language models, agents, orchestration frameworks, and enterprise integrations rather than purely oversight. The work centers on translating loosely defined business problems into trusted, production-ready AI solutions that measurably improve productivity, quality, cycle time, and decision-making within a mission-driven oncology research context. This is a remote position based in the United States; relocation assistance and visa sponsorship are not offered.

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, then convert successful pilots into scalable, production-grade solutions while owning monitoring, troubleshooting, performance tuning, and reliability - Build and maintain 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, including standardized patterns for agent architectures, retrieval-augmented generation, tool calling, multi-agent orchestration, and dev/test/prod promotion - Lead execution of high-impact AI and automation use cases such as case intake, triage, summarization, decision support, intelligent document processing, and embedded AI assistants integrated into enterprise systems - Define delivery plans with clear value metrics and success criteria, proactively surface technical risks and trade-offs, and ensure solutions comply with enterprise governance, security, and compliance standards at a lead level of accountability

Requirements

- Bachelor's degree required; Master's degree preferred - At least 7 years of experience in machine learning or closely related disciplines - Healthcare, life sciences, or clinical research domain experience and a track record delivering solutions in regulated, compliance-driven environments - Proven experience delivering complex, production-grade AI and automation solutions as a hands-on builder - Deep prompt engineering proficiency and demonstrated experience applying Generative AI to enterprise workflows - Strong programming skills in 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 the Microsoft AI ecosystem, such as Copilot Studio, Power Platform, Azure AI, or Azure OpenAI - Comfort owning ambiguous, high-visibility initiatives with minimal direction and aligning technical decisions with business outcomes in a matrixed environment

Nice to have

- Strong stakeholder influence skills and a record of translating concepts into shipped, adopted enterprise solutions - Ability to rapidly prototype while maintaining enterprise-grade security, reliability, and governance

Benefits and work setup

- Fully remote position based in the United States - Comprehensive total rewards benefits package supporting physical, mental, and financial well-being - Competitive compensation determined by experience, skills, performance, and market factors, with annual bonus and long-term incentive opportunities - Equal opportunity employer with a stated commitment to diversity and inclusion