AI Solutions Engineer

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.