AI Engineer

Role Purpose

The AI Engineer is responsible for developing and integrating practical AI solutions that support GREENFEED’s business and Digital/AI transformation initiatives.

The role will focus on building GenAI applications, RAG solutions, AI assistants/agents, and AI-enabled business applications, working closely with Data, Business, and Technology teams to bring AI use cases from idea to production.

Key Responsibilities

• Develop AI/GenAI applications using Large Language Models (LLMs).
• Build RAG-based solutions using enterprise documents, knowledge bases, and business data.
• Develop AI assistants and agents for business and internal productivity use cases.
• Integrate AI services with internal applications, APIs, databases, and enterprise platforms.
• Design prompts, workflows, tool/function calling, and AI application logic.
• Build backend services and APIs for AI applications.
• Evaluate and improve AI output quality, including accuracy, relevance, hallucination, response time, and cost.
• Support deployment, monitoring, troubleshooting, and continuous improvement of AI applications.
• Apply appropriate security, access control, data protection, and AI governance requirements.
• Work with Business, Data, and IT teams to turn business needs into practical AI solutions.

Requirements

• Bachelor’s degree in Computer Science, Software Engineering, Data Science, or related field.
• Around 2–4 years of relevant experience in software development, AI, data, or related technology roles.
• Good programming skills in Python.
• Hands-on experience with LLMs or GenAI applications.
• Understanding of: Prompt Engineering, RAG, Embeddings, Vector Search / Vector Database, AI Agent or Tool/Function Calling concepts
• Experience developing or integrating REST APIs.
• Basic SQL and database knowledge.
• Familiar with Git and standard software development practices.
• Good analytical and problem-solving skills.
• Able to learn new AI technologies quickly.

Key Competencies

• Strong problem-solving and hands-on engineering mindset
• Curious and willing to experiment with new AI technologies
• Able to translate business requirements into workable technical solutions
• Good teamwork and communication skills
• Focus on building practical, secure, and maintainable AI solutions

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