JOB OVERVIEW:

We are seeking an experienced IT Python and AI Programming Expert with demonstrated hands-on expertise in Python application development, data engineering, cloud deployments, and AI/ML solutioning. The ideal candidate must possess practical experience—not just training—in building and deploying Python solutions, working with large datasets, leveraging cloud services, and implementing AI/ML pipelines.

DESIRED QUALIFICATIONS:

• Hands-on experience building MCP servers and integration with Agentic AI workflows.
• Strong ability to communicate complex technical concepts to both technical and executive stakeholders.
• Proficiency in creating technical diagrams using Microsoft Visio or Draw.io.
• Experience in developing technical design and architecture documentation in Microsoft Word.
• Capability to build business and technical presentations using Microsoft PowerPoint.
• Expertise in creating data visualizations, charts, and reports using Microsoft Excel and Power BI.
• Strong verbal and written communication skills for management briefings, technical guidance, and report preparation.
• Experience using design patterns for scalable and maintainable solutions.
• Ability to clearly document code, models, and technical solutions.
• Proficiency in Generative AI and prompt engineering.
• Continuous learning and adaptability in large IT organizations.
• Strong troubleshooting skills for software and technical implementations in large-scale enterprise environments.
• Experience with API development and integration.
• Proficiency in querying and managing data in both SQL and NoSQL databases.

TECHNOLOGY IS OUR PASSION. PEOPLE ARE OUR PURPOSE.

We know tech, but we love people. NuAxis is home to thinkers and feelers, engineers and artists. We work hard and support each other along the way. Teamwork is more than just a buzzword for us; it’s a state of mind.
We believe happy employees do amazing work, so join our team NOW! We are currently seeking a talented and motivated IT Python and AI programming expert (SME) for a Full-Time position.

KEY RESPONSIBILITIES:

• Practical Application of Core Python Concepts:
• 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:
• Experience with data acquisition, cleaning, preprocessing, and transformation using Python tools and techniques for large scale datasets.
• Implementing and Deploying Cloud Applications:
• Deploying Python applications in cloud service production environments (e.g., AWS, Azure, GCP), including use of containerization tools (e.g., Docker, Kubernetes).
• Software Engineering Best Practices:
• Applying principles such as version control (Git), writing clear/testable code, participating in code reviews, and utilizing CI/CD pipelines.
• Knowledge of Data Science Best Practices:
• Experience in data pipelining, feature engineering, and creation of Machine Learning Models.
• Familiarity with Cloud-based Data Science Services:
• Proficiency in using managed AI/ML services from cloud platforms for developing, deploying, and managing data science applications.
• Ethical Practices and Security Knowledge:
• Demonstrated application of ethical guidelines in data science, including bias mitigation, data privacy, and secure coding practices in Python solutions.

TASKS MAY INCLUDE (BUT ARE NOT LIMITED TO):

• Data science tasks such as data acquisition, data cleaning, and feature extraction.
• Developing and demonstrating Proof-of-Concepts (PoC), independently or collaboratively.
• Creating technical diagrams and documentation to illustrate PoC and production implementations.
• Researching and presenting the latest tools/packages/capabilities to team members.
• Recommending relevant tools/packages for production environments.
• Collaborating with governance committees to document and obtain approvals for exploratory data science efforts.
• Consulting with architecture teams to identify automation solutions, including AI/ML integrations.
• Collaborating with cross-functional teams on holistic AI/ML solutions.