AI Engineer

Key Responsibilities

• Analyze business processes and stakeholder requirements to define clear system requirements, project scope, and success criteria.
• Design solutions and independently manage project plans, including priorities, timelines, milestones, dependencies, and risks.
• Develop and integrate end-to-end applications using AI-assisted development tools, covering frontend, backend, APIs, and databases.
• Review, validate, and debug AI-generated code to ensure quality, security, correctness, and maintainability.
• Ensure system security, data integrity, access controls, data validation, and proper backup procedures.
• Conduct system testing and coordinate UAT with stakeholders to ensure requirements and acceptance criteria are met.
• Manage deployment, go-live, documentation, and project handover, including formal stakeholder sign-off.
• Monitor project progress, communicate blockers and scope changes, and identify opportunities for continuous system improvement.

Required Qualifications

• Strong ability to analyze business processes and translate stakeholder needs into clear system requirements.
• Experience independently planning and managing projects from requirements through completion.
• Hands-on experience building end-to-end applications using AI-assisted coding tools.
• Good understanding of frontend, backend, databases, APIs, and system integration.
• Ability to review, debug, and validate AI-generated code.
• Knowledge of system security, access controls, data integrity, and backup practices.
• Experience with system testing, UAT, deployment, documentation, and user handover.
• Strong communication, problem-solving, analytical thinking, and ownership skills.

Skills: Artificial Intelligence, Deep Learning, Machine Learning, Natural Language Processing (NLP), Data Mining, Data Engineering, Computer Vision, Neural Network, Redis, Pattern Recognition