AI Engineer

Key Responsibilities

• Develop assigned AI and Generative AI use cases based on approved business requirements and technical designs.
• Build AI assistants, intelligent workflows and prototypes using Large Language Models and enterprise data.
• Prepare, process and analyze structured and unstructured data required for AI solutions.
• Develop and integrate RAG, prompt-engineering and AI-agent capabilities where applicable.
• Build and consume APIs to integrate AI solutions with internal applications and enterprise systems.
• Test and evaluate AI solution accuracy, quality, performance and expected business outcomes.
• Apply source-control, security, data privacy and responsible AI practices during solution development.
• Prepare technical documentation and support deployment, monitoring and production stabilization.

Education

Bachelor Degree in artificial intelligence, data science, computer science, software engineering, computer engineering or any related field.

Level of Experience

Fresh Graduate / Entry Level (0-1 year) in a related field. Relevant graduation projects, internships, hackathons or personal AI projects are considered an advantage.

Technical Skills & Knowledge

Essential

• Good understanding of AI, Machine Learning and Generative AI concepts.
• Ability to develop AI prototypes and translate business use cases into working solutions.
• Understanding of prompt engineering, LLM APIs and AI solution evaluation.
• Ability to work with structured and unstructured data using Python and SQL.
• Understanding of REST APIs and integration concepts.
• Basic knowledge of secure development, data privacy and responsible AI principles.
• Good analytical, problem-solving, communication and teamwork skills.

Desirable

• Exposure to RAG, embeddings, vector databases, AI agents and enterprise AI integration.

Certifications & Licensure

Essential

• Python programming
• Artificial Intelligence / Machine Learning fundamentals
• Generative AI and Large Language Models (LLMs) fundamentals
• SQL and data manipulation
• REST APIs and JSON
• Git / source control

Desirable

• Microsoft Azure AI Fundamentals (AI-900) or equivalent AI training/certification

Tools & Systems

Essential

• Python and common AI/data libraries
• LLM APIs and AI development frameworks
• SQL databases and SQL tools
• Git (GitHub/GitLab/Azure DevOps)
• Postman / Swagger
• Jira / Confluence or equivalent

Desirable

• Azure AI / Azure OpenAI or equivalent
• Vector databases
• Power BI
• Docker / CI/CD pipelines