AI Engineer

• Architect and implement scalable data pipelines and decision workflows using Python, with tools like PySpark and Pandas
• Convert complex operational policies and domain requirements into clear, testable logic and rule frameworks
• Create reusable, modular components that integrate into orchestrated production environments
• Incorporate AI or LLM-based services when needed, including prompt setup and structured response handling
• Ensure systems meet compliance and safety standards, including proper handling of sensitive data and validation of inputs/outputs
• Connect with internal and third-party APIs, designing for resilience with retries and error management
• Establish data quality checks, logging practices, and monitoring solutions to ensure system reliability
• Contribute to collaborative development workflows using Git (branching strategies, pull requests, peer reviews)
• Develop and manage CI/CD pipelines in Azure DevOps, including automated deployments and release tracking
• Diagnose and resolve issues in live systems to maintain operational continuity

• Strong professional experience building production-grade systems in Python
• Deep familiarity with PySpark and Pandas for large-scale data processing
• Demonstrated ability to design and implement rule-based or decision-driven systems
• Experience working with AI-assisted tools, agent-style systems, or automated workflows
• Solid grasp of version control practices using Git
• Practical experience with Azure DevOps, including pipeline creation and deployment oversight
• Background supporting and maintaining enterprise-level applications in production

• Experience in highly regulated or rules-intensive industries such as energy or utilities
• Familiarity with orchestration frameworks like Airflow or Azure Data Factory
• Exposure to real-world AI implementations in enterprise contexts

If interested in the role, please apply and email your most updated resume to Liam at [email protected].