Artificial Intelligence Engineer

Title: Senior AI Engineer Location: Eagan, MN (Remote) Duration: 6+ Months Description • Designs and develops scalable solutions using AI tools and machine-learning models. • Performs research and testing to develop machine learning algorithms and predictive models. • Utilizes big data computation and storage tools to create prototypes and datasets. Conducts model training and evaluation. Integrates, tests, tunes, and monitors solutions. • Proficient with multiple AI tools such as Python, Java, or R and machine learning frameworks like Spark, TensorFlow, or scikit-learn. Duties and Responsibilities Chosen resource must demonstrate these capabilities through actual work experience not merely training: Practical Application of Core Python Concepts: • Not just knowing Python syntax but demonstrating a track record of building and deploying Python applications or scripts that address IT operational needs, automate processes, or handle data management. Data Engineering and Analysis Skills: • Demonstrable experience with data acquisition, cleaning, preprocessing, and transformation using Python tools and techniques for building robust analysis on large scale data sets. Implementing and Deploying Cloud Applications: • Experience deploying python applications in cloud service production environments (e.g., AWS, Azure, GCP), potentially leveraging containerization tools (e.g., Docker, Kubernetes). Understanding of Software Engineering Best Practices: • Experience in applying principles like version control (Git), writing clear and testable code, participating in code reviews, and using continuous integration/continuous deployment (CI/CD) pipelines. Knowledge of Data Science Best Practices: • Demonstrated understanding and implementation of data science solutions such as data pipelining, feature engineering, or creation of Machine Learning Models. Familiarity with Cloud-based Data Science Services: • Proficiency using managed AI/ML services provided by cloud platforms to streamline development, deployment, and management of data science applications. Ethical Practices and Security Knowledge: • A demonstrated awareness and application of ethical guidelines for data science solutioning, including addressing bias, ensuring data privacy, and implementing secure coding practices in Python-based solutions. • An individual whose qualifications and/or particular expertise are exceptional and/or highly specialized or unique. and are typically identified as recognized industry leaders: and typically initiates, supervises, and/or develops requirements from a project's inception to conclusion for complex to extremely complex programs. and also provides strategic and expert advice and technical guidance, to program and project staff. • This individual also provides detailed analysis, evaluation and recommendations for improvements, optimization development, and/or maintenance efforts for client-specific or mission critical challenges/issues and consults with client to define needs or challenges. while also supervising studies: leading surveys and performing data collection for analyses used to advise and recommend/suggest solutions. Chosen resources should exhibit through actual work experience not merely training: o Desirable: hands on experience building MCP servers and integration with Agentic AI workflows. o Communicating complex technical concepts to both technical and executive stakeholders. o Proficiency creating technical diagrams with products like Microsoft Visio or Draw.io. o Proficiency creating technical design and architecture documents in Microsoft Word. o Proficiency creating business and technical presentations in Microsoft PowerPoint. o Proficiency creating data representations, charts and reports in tools such as Microsoft's Excel worksheets and Power BI. o Ability to communicate, orally and in writing, sufficient to develop and present management briefings; provide written and/or verbal guidance on technical issues; and prepare/present recommendations and reports. o Using design patterns for building scalable and maintainable applications/solutions. o Clearly document code, models, and technical solutions. o Proficiency in Generative AI and prompt engineering. o Continuous learning and adaptability in a very large IT organization. o Troubleshooting software and technical implementations in large-scale enterprise ecosystems. o API development and integration. o Querying and managing data in both SQL and NoSQL databases. • Tasks – might include (neither exhaustive nor restrictive): o Data science tasks such as data acquisition, data cleaning, and feature extraction. o Develop and demonstrate proof-of-concepts (PoC); independently or in a team. o Create technical diagrams and documentation to show PoC implementations and potential production implementation. o Researching and presenting to teammates on the latest tools/packages/capabilities being developed. o Make recommendations on relevant tools/packages to use for production environments. o Work with relevant governance committees to document and obtain approval for exploratory data science efforts. o Consulting with members of architecture teams to identify potential automation solutions which may include AI/ML. o Collaborating with cross functional teams on holistic AI/ML solutions. Education: o Over Twenty (20) years' of relevant experience. o A degree from an accredited College/University in the applicable field of services is preferred. Four additional years of relevant experience in lieu of a college degree is required. If the individual's degree is not in the applicable field then four additional years of related experience is required.