Application Developer AI

We are seeking an AI Application Developer to help build and deploy practical AI solutions that improve productivity across operations, project management, and business workflows. This is a hands‑on role focused on implementing AI tools, automation, and integrations — not research.

You will work with internal stakeholders to develop AI‑powered assistants, automate manual processes, and integrate AI into existing business systems.

This is an excellent opportunity for someone early in their career who wants to gain real‑world experience building and deploying AI solutions.

• Design, build, and deploy AI/ML models to support business operations
• Develop automation using LLMs, machine learning, and AI workflows
• Build AI agents for internal productivity and decision support
• Implement document intelligence and data extraction solutions
• Develop predictive analytics models where applicable

• Integrate AI solutions with field operations systems
• Build APIs and automation pipelines
• Connect AI solutions to internal databases
• Prepare datasets for training and inference
• Clean and normalize structured and unstructured data
• Build data pipelines for AI workloads

• Follow the company AI governance and security standards
• Ensure data privacy and compliance requirements are met
• Monitor AI outputs for accuracy and reliability
• Implement human‑in‑the‑loop controls where required
• Work with department leaders to identify AI opportunities
• Translate business problems into technical AI solutions
• Provide demonstrations and prototypes
• Support change management and adoption
• Monitor performance of deployed AI models
• Improve prompts, workflows, and models

• Bachelor's degree in Computer Science, AI, Engineering, or related field
• Equivalent practical AI experience considered

• 2–5 years experience in AI / Machine Learning / Automation
• Experience with APIs and system integrations
• Experience working with business stakeholders.

• AI agents / workflow automation
• Model evaluation and tuning

• Hugging Face (nice to have)
• Azure Functions / Logic Apps
• Docker (nice to have)

• Structured and unstructured data handling

• AI solutions deployed to production
• Business hours saved through automation
• Accuracy of AI outputs
• ROI of AI initiatives