Engineer, Senior AI; IT Python and AI programming; Expert III

Engineer, Senior AI (IT Python and AI programming (Expert) III

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Engineer, Senior AI (IT Python and AI programming (Expert) III). Design and develop scalable AI solutions, leverage machine-learning models, and contribute to an IT architecture roadmap to support the Customer mission. The CASI team leads evaluation and implementation of innovative solutions for technology infrastructure and application architecture.

• 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.
  • Typically performs all functional duties independently.

• Chosen resource should exhibit through actual work experience not merely training:
  • Desirable: hands on experience building MCP servers and integration with Agentic AI workflows.
  • Communicating complex technical concepts to both technical and executive stakeholders.
  • Proficiency creating technical diagrams with products like Microsoft Visio or Draw.io.
  • Proficiency creating technical design and architecture documents in Microsoft Word.
  • Proficiency creating business and technical presentations in Microsoft PowerPoint.
  • Proficiency creating data representations, charts and reports in tools such as Microsoft s Excel worksheets and Power BI.
  • 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.
  • Using design patterns for building scalable and maintainable applications/solutions.
  • Clearly document code, models, and technical solutions.
  • Proficiency in Generative AI and prompt engineering.
  • Continuous learning and adaptability in a very large IT organization.
  • Troubleshooting software and technical implementations in large-scale enterprise ecosystems.
  • API development and integration.
  • Querying and managing data in both SQL and No
    
    SQL databases.

• Data science tasks such as data acquisition, data cleaning, and feature extraction.
• Develop and demonstrate proof-of-concepts (PoC); independently or in a team.
• Create technical diagrams and documentation to show PoC implementations and potential production implementation.
• Researching and presenting to teammates on the latest tools/packages/capabilities being developed.
• Make recommendations on relevant tools/packages to use for production environments.
• Work with relevant governance committees to document and obtain approval for exploratory data science efforts.
• Consulting with members of architecture teams to identify potential automation solutions which may include AI/ML.
• Collaborating with cross functional teams on holistic AI/ML solutions.

A minimum of eight (8) to twelve (12) years  relevant experience.

o A degree from an accredited College/University in the applicable field of services is required. If the individual s degree is not in the applicable field then four (4) additional years of related experience is required.

o

Note:

Special credentials (licenses and/or certifications) may be required at the Task Order level on a case-specific basis.

• Pass both a client mandated clearance process to include drug screening, criminal history check and credit check.
• Once a candidate s resume is approved and interview passed, the agency is responsible for providing drug screening. Failure to submit the drug screening results will delay the security…