Enterprise AI Developer

Reporting to the Enterprise AI Manager, the Enterprise AI Developer will be responsible for implementing Enterprise AI solutions by focusing on system integration first before AI model development, and delivering Enterprise AI projects, such as an Agentic AI framework and Agentic Systems, while supporting our organization with implementations in Software Development/Low-Code No-Code Tools such as Power Platform. The role requires proficiency in Python and JavaScript for AI integration, but additional programming languages may be needed depending on system requirements. The key focus is ensuring AI-driven automation aligns with enterprise workflows through efficient system and API integrations.

Software and AI Model Development and Integration

• Design and build Agentic AI solutions using existing LLMs and integrate them with Enterprise Applications/Systems where applicable.
• Build and deploy machine learning models into production environments integrated with enterprise systems like Power Platform.
• Analyze and improve ML algorithms for efficiency while ensuring compatibility with Enteprise AI workflows or embedded apps in our platforms (SAP, Salesforce, Microsoft).

Documentation

• Create comprehensive documentation for all deployed solutions including integration points with the different platforms our solutions are connecting with.

Strategy Implementation

• Translate group-level technical strategies into actionable implementations for AI/ML systems and enterprise automation workflows.

Technology Evaluation

• Evaluate different technology choices (including Power Platform capabilities) and select the most suitable for specific problems with sound tradeoffs.

PaaS Development

• Promote a Platform-as-a-Service (PaaS) mindset to enable scalable, reusable solutions across AI solutions (apps and workflows)

REQUIRED SKILLS

AI/ML Expertise

• Proficiency in designing automated training pipelines and deep understanding of machine learning models.
• Excellent understanding of common ML model classes (e.g., tree-based models, statistical models)

Software Engineering

• Ability to design core modules/components of complex products/platforms while contributing to development tasks.

Programming

• Advanced Python skills with proficiency in AI platforms such as LangChain, LangGraph, and ML frameworks such as TensorFlow or PyTorch.

DevOps

• Working knowledge of DevOps practices such as CI/CD pipelines and containerization tools (e.g., Docker)

Problem Solving

• Ability to work on complex coding tasks with long-term solution-driven scope.

Power Platform Expertise

• Experience creating workflows in Power Automate or embedding ML models into apps built using Power Apps.

Behavioral Skills

• Ability to functionally decompose complex problems into simple, straightforward solutions
• Have a complete understanding of the various application/ system interdependencies and limitations
• Ability to operate and innovate in a lean team with a fast-paced environment, balancing both strategic and tactical needs
• Detailed-oriented and the ability to spot and fix errors in complex code
• Analytical and critical problem-solving abilities
• Ability to perform tasks independently