AI Engineer, Sr

A-dec•Newberg, OR

23h

About The Position

At A-dec, we do more than create the highest quality products and services for the dental industry; we strive to deliver a superior employment experience for each of our team members. With an environment that encourages and assists each person in developing to their highest potential, a career at A-dec is incredibly rewarding. Overview The AI Engineer, Sr plays a key role in building and scaling applied artificial intelligence capabilities across the organization. This role focuses on delivering practical AI solutions that drive automation, improve decision making, and enable predictive insights across business functions such as supply chain, finance, operations, sales, and customer service. The AI Engineer, Sr will design, build, and deploy AI powered systems including predictive models, forecasting solutions, and agentic AI workflows. This is a hands-on engineering role that partners closely with business and technology teams to turn real world problems into scalable AI solutions. The role emphasizes production ready systems, responsible AI use, and measurable business impact rather than academic research.

Requirements

Programming languages : Python for building AI models, automation, and production services
SQL for working with structured data used in analytics, forecasting, and model inputs
Technical Skills : Strong understanding of data pipelines, feature engineering, and data quality fundamentals
Experience integrating AI solutions with existing enterprise systems using APIs
Familiarity with cloud-based AI services and deployment patterns
Applied model evaluation and testing expertise, including prompt testing, experimentation and A/B testing, system integration testing and production monitoring.
Experience optimizing costs for LLMs and agentic systems in cloud environments, including inference efficiency, token usage, and model selection tradeoffs
Understanding of software engineering best practices including version control, testing, and documentation
Knowledge of security, privacy, and responsible AI considerations in business environments
Bachelor’s degree in computer science, engineering, data science, mathematics, or a related technical field, or equivalent practical experience
Successful candidates typically possess over 8 years of relevant professional or technical engineering experience of increasing responsibility and difficulty of assignments.
Experience building and deploying applied AI or machine learning solutions in production environments
Hands on experience with at least one machine learning framework such as scikit learn, PyTorch, or TensorFlow
Practical experience using large language models via APIs for real world business use cases
Experience designing and implementing AI driven automation or agentic workflows

Nice To Haves

Programming Languages : JavaScript or TypeScript for integrating AI capabilities into web applications or internal tools
Bash or shell scripting for automation and deployment tasks
Technical Skills : Experience with agentic AI frameworks or orchestration tools such as LangChain, LlamaIndex, AutoGen, or MCP based patterns
Experience with cloud platforms such as Azure, AWS or GCP beyond basic usage
Familiarity or experience with Dynamics 365, Snowflake and Microsoft Fabric
Familiarity with MLOps practices including model monitoring, versioning, and lifecycle management
Applied statistics and model evaluation skills, including experiment design and statistical validation, to ensure reliable and unbiased AI driven decision support and forecasting.
Experience evaluating and integrating third party AI platforms or vendors
Exposure to automation platforms, RPA tools, or workflow engines where AI is embedded into business processes
Familiarity with emerging AI regulations and auditability techniques
Ability to mentor or guide others on applied AI best practices

Responsibilities

Design, develop, validate and deploy AI driven solutions that support automation, predictive analytics, forecasting, and decision support across the business
Build and maintain machine learning models and AI services used in production environments
Design and orchestrate multi agent AI systems, including LLM based agents, agent routing and collaboration, and MCP enabled data and tool APIs for secure, scalable enterprise workflows
Build and optimize LLM capabilities using retrieval augmented generation, model fine tuning, and interface integration to deliver reliable, high quality AI outputs in production environments
Integrate AI capabilities with existing enterprise systems such as ERP, CRM, data platforms, and workflow tools
Implement data pipelines and feature engineering processes to support reliable model training and inference
Evaluate and integrate third party AI platforms, APIs, and tools where appropriate
Establish best practices for model deployment, monitoring, performance tuning, and lifecycle management
Support enterprise data governance by partnering with data owners to define data contracts and ensure data quality and consistency across pipelines
Ensure AI solutions meet security, privacy, and responsible AI standards
Collaborate with software engineers, data engineers, and IT teams to ensure scalable and maintainable implementations
Measure and communicate business impact of AI solutions using clear metrics and outcomes
Document system designs, models, and operational processes to support knowledge sharing and scalability
Manages, leads, and/or assists various new or sustaining technology projects; performs light project management duties as required.
Stay current with applied AI trends and recommend practical innovations that align with business goals