The AI Solutions Engineer will be embedded within Mirion’s Medical business units and partners directly with manufacturing, quality, service, and business teams to identify opportunities for improvement and deliver AI-driven solutions that produce measurable operational results. The ideal candidate combines strong software engineering skills with hands-on AI expertise and thrives in fast-paced environments where business impact is the primary measure of success.
Reporting directly to the Chief AI & Digital Officer, this position offers direct exposure to enterprise AI strategy while providing the autonomy to build and deploy solutions that improve how the business operates.
Key Areas of Responsibility:
Identify and Prioritize Business Opportunities
- Embed within Medical business units to develop a deep understanding of operational workflows, challenges, and priorities.
- Participate in leadership meetings, observe manufacturing operations, and collaborate closely with quality, service, engineering, and product teams.
- Identify manual, repetitive, error-prone, or inefficient processes that may benefit from automation or AI-driven improvements.
- Translate business challenges into clearly defined technical solutions and develop business cases that support prioritization and investment.
Design, Develop, and Deploy AI Solutions
- Design and implement AI-powered applications that address operational challenges across manufacturing, quality, service, and administrative functions.
- Develop computer vision solutions for applications such as visual inspection, defect detection, anomaly identification, and image-based quality assurance.
- Build and deploy agentic AI and large language model (LLM)-based solutions to automate workflows, enhance decision-making, and improve operational efficiency.
- Own the full product lifecycle, including solution design, prototyping, pilot implementation, production deployment, user adoption, and ongoing improvement.
- Leverage enterprise platforms, services, and standards while maintaining a rapid, solution-oriented delivery approach.
Adoption and Business Impact
- Communicate project objectives, progress, risks, and outcomes to business stakeholders in clear, non-technical language.
- Define success measures and monitor key performance indicators such as cycle time, throughput, quality, productivity, error reduction, and cost savings.
- Provide training, support, and change management guidance to encourage adoption and long-term success.
- Continuously evaluate deployed solutions and implement enhancements based on user feedback and business needs.
Collaborate Across the Enterprise
- Partner with the Chief AI & Digital Officer and the broader AI & Digital organization to align with enterprise architecture, security, governance, and technology standards.
- Share best practices, reusable solutions, and implementation patterns that can be leveraged across business units.
- Ensure solutions meet quality, validation, documentation, and regulatory requirements applicable within a medical and regulated environment.
- Collaborate effectively with Quality, Regulatory, Engineering, IT, and Operational teams.
Knowledge, Skills & Abilities:
- Bachelor’s degree in Computer Science, Engineering, Data Science, Artificial Intelligence, or a related technical discipline, or equivalent practical experience.
- Minimum of 5 years of experience developing and deploying production software, machine learning, or AI-based solutions.
- Experience with software engineering and cloud-based application development and deployment.
- Hands-on experience designing and implementing agentic AI or LLM-based solutions using platforms such as LangChain, LangGraph, AutoGen, or similar frameworks.
- Strong programming experience in Python and familiarity with APIs, cloud architectures, and production deployment practices.
- Experience working with cloud platforms such as Microsoft Azure, Amazon Web Services (AWS), or Google Cloud Platform (GCP).
- Working knowledge of DevOps, MLOps, software deployment, monitoring, and maintenance practices.
- Demonstrated ability to independently identify opportunities, define solutions, and successfully execute complex projects with minimal supervision.
- Excellent communication and stakeholder management skills, including the ability to explain technical concepts to non-technical audiences.
- Ability to thrive in ambiguous environments and work independently while collaborating with cross-functional teams.
Preferred Qualifications
- Experience developing computer vision solutions using technologies such as OpenCV, PyTorch, TensorFlow, or equivalent frameworks.
- Experience with Azure AI, AWS Bedrock, Databricks, OpenAI, Claude, or similar AI platforms and services.
- Experience within regulated industries such as medical devices, healthcare, pharmaceutical, life sciences, or highly regulated manufacturing environments.
- Familiarity with quality management systems and regulatory frameworks, including ISO 13485, FDA QSR, or QMSR requirements.
- Experience serving as an embedded, customer-facing, forward-deployed, or solutions-focused engineer.
- Knowledge of radiation therapy, nuclear medicine, dosimetry, diagnostic imaging, or related healthcare technologies.
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