AI Fleet Engineer

About STYL Solutions Ride on the wave of Industry 4.0! Join STYL Solutions in the forefront of using Fintech and IoT technologies for smart city/nation transformation. Headquartered in Singapore with R&D center in Vietnam, STYL Solutions designs, develops, and supplies hardware, software and integrated solutions for applications in payment, loyalty management, location tracking, self-service operation, telemetry. Our market segment coverage extends from financial services, retail, mass transit, education to social services markets in Singapore and South Asia Pacific. Our vision is to use Fintech and IoT to create smart and efficient cities that enhance Quality of Life through convenience and healthier living. Job Description STYL Solutions has transitioned beyond conventional manual programming to implement industrialized production environments. Hence, we are looking for a self-driven AI Fleet Engineer who can orchestrate a fleet of specialized AI agents to architect, deliver, and maintain robust high-quality enterprise software solutions, moving beyond individual contribution to strategic systems oversight. You will act as a "commander" - technical strategist rather than a standard software engineer, stepping away from the traditional role of an individual contributor. Your core objectives involve defining architectural outcomes, managing agent iterations, and ensuring the integrity of large-scale software systems. Responsibilities Orchestrate Code Production Lines: Direct an autonomous fleet of specialized AI coding agents, managing their context, prompting loops, and sequence dependencies to generate robust feature modules, microservices, and end-to-end applications. Specification-Driven Development (SDD): Author and refine clean, precise, machine-readable blueprints (API/AsyncAPI schemas and custom Agent Manifests) that serve as the strict ground truth and operating boundaries for your agent fleet. Git Workflow & Release Management: Manage complex, automated Git workflows. Oversee the automated branches, pull-requests, and merge conflicts generated by your agents, ensuring parallel development pipelines integrate cleanly with standard enterprise deployment targets. Build Skills & Tools: Identify gaps where frontier AI models reach a system boundary or logic limitation. Step in to programmatically build and inject custom Skills and Tools (such as specialized API wrappers or database connectors) into the fleet's registry to unblock automation. Continuous Tool Adaptation: Constantly test, evaluate, and adopt emerging developer tools, coding harnesses, and week-by-week upgrades in frontier AI models to maintain maximum pipeline throughput and software reliability. Production Fleet Operations: Deploy, configure, and monitor post-implementation support agents, Automated Root Cause Analysis (RCA) loops, and synthetic monitoring agents on live production environments. Job Requirements Bachelor's degree in Computer Science, Software Engineering, or AI-related studies preferred; Master's Degree will be advantageous At least 1-3 years working experience in a Al development or similar role. Strong Engineering & Git Literacy : Proven experience working within modern enterprise software teams, with advanced mastery of Git workflows (branching, trunk development, PR validation, and GitOps models). AI-Native Workflow Experience : Proven experience utilizing AI-assisted coding tools, multi-agent frameworks, LLM prompting loops, or automated testing harnesses in daily development workflows. Schema-First Mindset : Strong familiarity with Specification-Driven Development (SDD), including drafting and validating OpenAPI, AsyncAPI, or JSON schemas. Systems Thinking & Adaptability : Passionate about technical horizon-scanning; able to quickly pivot, experiment with, and master new development tools released by the global software community. What measures the role’s success Pipeline Efficiency & Throughput System Reliability & Quality based on defect density and stability of code modules generated by the AI fleet and effectiveness of Automated Root Cause Analysis (RCA) loops in identifying and resolving production issues without human intervention. Accuracy and completeness of Specification-Driven Development (SDD) artifacts (e.g., OpenAPI/AsyncAPI schemas). Success rate of agent execution against the defined 'ground truth' blueprints. GitOps & Integration Integrity: Overall health of automated CI/CD workflows Tooling & Innovation A…