Senior AI (IT Python and AI programming (SME))

Job Title: Senior AI (IT Python and AI programming (SME))

Location: 100% Remote / Eagan, MN
Duration: 12+ months contract

Over Twenty (20) years of relevant experience.

Summary

Client CIO Architecture, Strategy & Innovation (CASI) is responsible to assist Vice President of Information Technology (IT) design, develop, maintain, support, and translate corporate business vision and strategy along with stakeholder input into objectives for building, enhancing, or replacing business and IT systems capabilities, together with an implementation of a comprehensive IT roadmap, all-the-while maintaining resilience to change as a key architectural and strategy objective for the enterprise. In the fast-paced world of IT, agility and responsiveness to the frequently occurring changes in direction are a must, even while moving continuously forward implementing elements of the Postmaster General s Delivering for America 10-year plan.

To support the client s mission, projects, and system requirements, the client requires sophisticated information technology systems support services by experienced professionals. The CASI team demonstrates leadership by evaluating and driving implementation of innovative solutions for technology infrastructure and application architecture.

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: Track record of building and deploying Python applications or scripts addressing IT operational needs, automation, or data management.

• Data Engineering and Analysis Skills: Experience with data acquisition, cleaning, preprocessing, and transformation for large-scale datasets.

• Implementing and Deploying Cloud Applications: Experience deploying Python apps in cloud environments (AWS, Azure, Google Cloud Platform) using Docker, Kubernetes.

• Software Engineering Best Practices: Use of Git, writing testable code, code reviews, and CI/CD pipelines.

• Data Science Best Practices: Data pipelining, feature engineering, building Machine Learning Models.

• Cloud-based Data Science Services: Proficiency with managed AI/ML services from cloud platforms.

• Ethical Practices and Security: Knowledge of bias mitigation, data privacy, secure coding practices.

• An individual whose qualifications are exceptional or highly specialized; initiates, supervises, and develops requirements for complex programs; provides strategic advice, technical guidance, analysis, evaluation, and recommendations for improvements; consults with client to define needs and supervise studies, surveys, and data collection.

Chosen resource should exhibit through actual work experience not merely training:

• MCP server building and Agentic AI workflow integration (Desirable).

• Technical communication to both technical and executive stakeholders.

• Technical diagrams creation (Microsoft Visio, Draw.io).

• Technical design & architecture documentation (Microsoft Word).

• Presentations creation (Microsoft PowerPoint).

• Data representation and reporting (Excel, Power BI).

• Design patterns for scalable and maintainable applications.

• Clear code/model documentation.

• Generative AI and prompt engineering proficiency.

• Continuous learning in large IT environments.

• Troubleshooting in enterprise ecosystems.

• API development and integration.

• Querying and managing SQL and NoSQL databases.

Tasks might include (neither exhaustive nor restrictive):

• Data acquisition, cleaning, feature extraction.

• Proof-of-concepts (independent or team-based).

• Technical diagrams and documentation for PoCs and production.

• Research and present emerging tools/packages.

• Recommendations for production tool usage.

• Work with governance committees for exploratory AI/ML efforts.

• Consult with architecture teams for automation including AI/ML.

• Collaborate on holistic AI/ML solutions.

Education

• Over Twenty (20) years of relevant experience.

• Degree from an accredited institution preferred; additional four years of experience required without a degree or if degree not in applicable field.