Junior AI Engineer: Build Agents & Automations

Axos Business Center, Corp

Manila

On-site

PHP 700,000 - 1,100,000

Full time

14 days+

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Job summary

Axos Business Center, Corp is offering a role to deepen your AI engineering expertise with a hands-on position alongside experienced AI engineers. You will work on AI-driven solutions that transform software development and automate processes, gaining hands-on experience with Claude and building intelligent agents under strong mentorship.

The opportunity focuses on learning across the AI stack, with emphasis on prompts, MCP servers, and integrations with internal platforms.

Qualifications

1-2 years of hands-on software development or entry-level AI/ML roles.
Bachelor's Degree in CS, IT, Mathematics, or related discipline (or equivalent).
Nice to Have Python or JavaScript programming experience.
Familiarity with API integrations and REST/GraphQL services.
Experience with CI/CD pipelines, GitHub Actions, or similar automation tools.
Understanding of software testing practices and quality metrics.
Exposure to Large Language Models (LLMs) or prompt engineering.
Basic knowledge of agentic systems and workflow automation.
Exposure to financial services or banking industry.
Qdrant vector database experience or familiarity.
Databricks exposure or knowledge of data engineering platforms.

Responsibilities

Assist in designing and deploying AI agents for specific business domains under guidance of senior engineers.
Develop and refine prompts under supervision, learning best practices for domain-specific AI outputs.
Build and test integrations between AI systems and internal platforms (GitHub, Azure DevOps, Linear, Confluence).
Support implementation of Model Context Protocol (MCP) servers with code review and validation.
Create and maintain AI skills and plugins for consumption by development teams with feedback from senior engineers.
Analyze AI model outputs for quality and accuracy; document findings and iterate on improvements.
Develop testing strategies for AI-generated code and documentation with established frameworks.
Learn and apply KPI and ROI measurement practices for AI systems.
Collaborate with software teams to identify automation opportunities and discuss agentic workflow designs.
Build and test proof-of-concepts to validate AI approaches with senior oversight.
Document your learning, workflows, and implemented solutions for team knowledge sharing.
Support discovery and requirements gathering for new AI-driven solutions.