Senior Software Engineer

Core Profile

The Senior Software Engineer – Enterprise AI is responsible for delivering AI-driven solutions with a strong emphasis on system and API integration. This role plays a key part in building agentic AI systems and frameworks that enhance enterprise workflows. The engineer will contribute to both AI solution development and broader software engineering efforts, integrating AI/ML models into enterprise platforms. Proficiency in Python and JavaScript is required, with the flexibility to work across other languages and tools as needed by system requirements.

Nature of Work

Software and AI Integration

• Design and implement AI solutions using existing LLMs and integrate them into enterprise systems and applications.
• Develop and deploy machine learning models in production environments, ensuring compatibility with enterprise platforms such as SAP, Salesforce, Microsoft, and internal services (e.g., Java/Spring, Node.js).
• Optimize ML models and algorithms to align with enterprise performance and integration requirements.

Documentation

• Create clear, comprehensive technical documentation for AI solutions, including integration points with enterprise systems.

Strategy Execution

• Implement technical strategies developed by the group or team lead, translating them into practical software and AI/ML solutions.

Technology Evaluation

• Compare and assess technical tools, libraries, and platforms—including Power Platform components—based on project requirements, making informed tradeoffs in implementation decisions.

Platform-as-a-Service (PaaS) Development

• Contribute to building reusable, modular AI components that support scalable enterprise-wide applications and workflows.

Displayed Skill Mastery

AI/ML Expertise

• Experience designing and managing automated ML pipelines and workflows.
• Understanding of key ML model types (e.g., tree-based models, statistical models).

Software Engineering

• Ability to contribute to and design complex modules in enterprise-scale systems.
• Familiar with integration patterns for AI/ML features within enterprise applications.

Programming

• Proficient in Python and JavaScript; hands-on experience with frameworks like LangChain, LangGraph, TensorFlow, or PyTorch.

DevOps

• Working knowledge of CI/CD pipelines, version control, and containerization (e.g., Docker).

Power Platform

• Experience working with Power Automate and Power Apps, especially in embedding AI workflows.

Problem Solving

• Skilled in breaking down complex software and AI challenges into manageable solutions.

Behavioral Skills

• Strong attention to detail and problem-solving mindset.
• Ability to work independently and collaborate effectively within cross-functional teams.
• Comfortable navigating system dependencies and technical constraints.
• Clear communicator with the ability to document and present technical work.

Expected Results

• Deployment of agentic AI systems integrated into enterprise business processes.
• High-quality, maintainable code contributions supporting enterprise applications.
• Measurable improvement in the accuracy and performance of deployed AI/ML models.
• Reusable code and AI components for use within enterprise platforms (e.g., Salesforce, SAP, Microsoft).
• Clear technical documentation of integration architecture and development practices.
• Development of accessible APIs or embedded capabilities for AI/ML solutions.
• Timely delivery of new features and applications that meet stakeholder expectations.
• Resolution of assigned service desk tickets and adherence to SLAs.
• Delivery of audit and compliance-related documentation as required.

Required Qualifications

Education:

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related field.

Experience:

• Minimum of 5 years of software development experience, with a focus on AI/ML integration and enterprise system development.

Technical Skills:

• Proficiency in Python and JavaScript.
• Hands-on experience developing and deploying ML pipelines.
• Familiarity with enterprise systems such as SAP, Salesforce, Microsoft, and low-code platforms (e.g., Power Platform).

Adaptability:

• Comfortable working across new and legacy systems and integrating them into modern enterprise platforms.