Agentic AI Engineer

Salary: ₱70,000 – ₱100,000 per month

Key Responsibilities

• Design, develop, test, and deploy Agentic AI solutions using LLMs and agent development frameworks.

• Build autonomous AI agents capable of reasoning, planning, tool calling, and multi-step task execution.

• Develop and manage multi-agent workflows and orchestration systems.

• Integrate AI agents with enterprise applications, REST APIs, databases, and cloud services.

• Implement memory management, context handling, retrieval-augmented generation (RAG), and knowledge-grounding capabilities.

• Develop AI-powered automation solutions to streamline business processes and operational workflows.

• Implement Responsible AI practices, security controls, governance, and compliance measures throughout the AI solution lifecycle.

• Conduct testing, evaluation, monitoring, debugging, and performance optimization of AI agents in production environments.

• Collaborate with business stakeholders, architects, and engineering teams to identify business use cases and deliver Agentic AI solutions.

• Create technical documentation, reusable components, development standards, and best practices for AI agent development.

• Continuously evaluate emerging AI technologies, frameworks, and techniques to improve solution quality and efficiency.

Qualifications and Experience

• Bachelor's degree in Computer Science, Information Technology, Software Engineering, Artificial Intelligence, or a related field, or equivalent practical experience.

• 5–7 years of overall relevant software development and engineering experience, with substantial hands-on experience in Python and Agentic AI development.

• Demonstrated experience developing, integrating, and deploying LLM-powered applications or AI agents.

• Understanding of the software development lifecycle, AI solution architecture, testing, deployment, and production support.

• Strong hands-on experience in Agentic AI development and AI-powered application engineering.

• Proficiency in Python for AI development, backend integration, and workflow automation.

• Practical experience with LLMs, prompt engineering, and tool/function calling.

• Experience building AI agents capable of planning, reasoning, and executing multi-step tasks.

• Understanding of agent orchestration, API integration, and enterprise system connectivity.

• Knowledge of RAG, embeddings, vector databases, and knowledge-grounding techniques.

• Strong analytical, problem-solving, debugging, and troubleshooting skills.

• Excellent technical, verbal, and written communication skills.

• Ability to collaborate effectively with technical teams and business stakeholders.