Senior AI Engineer, Enterprise Agentic Solutions

SOLVENTUM•Remote - Minnesota, MN

1d•$142,800 - $196,350•Remote

About The Position

At Solventum, we enable better, smarter, safer healthcare to improve lives. As a new company with a long legacy of creating breakthrough solutions for our customers’ toughest challenges, we pioneer game-changing innovations at the intersection of health, material and data science that change patients' lives for the better while enabling healthcare professionals to perform at their best. Because people, and their wellbeing, are at the heart of every scientific advancement we pursue. We partner closely with the brightest minds in healthcare to ensure that every solution we create melds the latest technology with compassion and empathy. Because at Solventum, we never stop solving you. The Impact You’ll Make in this Role As a Senior AI Engineer, Enterprise Agentic Solution, you will serve as the premier technical authority driving the enterprise-wide architecture, engineering, and deployment of Agentic AI and Generative AI platforms. Operating at a highly senior level, your focus extends beyond data science and model training into the rigorous engineering of scalable, high-performance AI systems. You will architect robust, multi-agent frameworks that integrate seamlessly into mission-critical healthcare operations. Furthermore, you will act as a primary technical liaison, partnering directly with executive stakeholders and healthcare customers to translate complex business challenges into highly reliable, autonomous AI solutions.

Requirements

Bachelor's degree in Computer Science, Software Engineering, AI, or related field AND 8+ years of professional experience in software engineering and ML/AI development OR a Master's degree AND 6+ years of experience.
Deep, hands-on programming expertise in Python and extensive experience building backend systems and APIs.
Direct experience developing and deploying Agentic workflows and orchestration frameworks (e.g., AutoGen, LangChain) in production.
Strong practical understanding of Generative AI paradigms, prompt engineering, and LLM evaluation metrics.
Experience building ML infrastructure and deploying applications using cloud-native technologies (AWS, Azure, or GCP)

Nice To Haves

Hands-on experience implementing Graph RAG and complex document parsing workflows.
Experience with healthcare data standards (e.g., FHIR) and secure data handling practices.
Strong background in system design patterns, microservices, and infrastructure as code.
Demonstrated ability to lead development pods and translate complex business requirements into technical deliverables.

Responsibilities

Build, test, and deploy autonomous, multi-agent systems using frameworks such as AutoGen and LangGraph.
Implement the core logic for agent orchestration, tool utilization, and state management.
Engineer robust data ingestion pipelines capable of processing complex, multi-modal healthcare data.
Implement advanced retrieval techniques, including Graph RAG, and develop solutions for high-accuracy document intelligence (e.g., page-by-page parsing of complex PDFs).
Design and execute prompt engineering strategies.
Establish and monitor rigorous evaluation of metrics for LLM performance to ensure clinical safety, minimize hallucinations, and optimize inference latency in production environments.
Partner with data scientists, product managers, and cloud engineers to transition AI models into high-concurrency production environments.
Establish code quality standards, write comprehensive technical documentation, and mentor junior developers.
Build and maintain MLOps pipelines, ensuring secure containerization, CI/CD integration, and comprehensive system telemetry in adherence to healthcare privacy regulations (HIPAA, HITRUST).