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Full Stack (AI) Technical Lead

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Onsite

Full Stack (AI) Technical Lead

White Cloak Technologies, Inc.

Full Stack (AI) Technical Lead

Skills

Google Cloud PlatformDockerReactJavaTesting & QAMicroservicesSpring BootAIAWSGitHubKubernetesAzure

1 month ago

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Important information


Contract type:

Permanent

Location:

Pasig, Metro Manila, Philippines

Work mode:

Onsite

Published on:

24 September 2026

What they need


The Full Stack Technical Lead will lead the technical design, development, and delivery of modern full-stack applications, combining hands-on engineering with technical leadership. Working with Product Managers, Business Analysts, QA, DevOps, and other stakeholders, the role drives architecture and engineering best practices while guiding developers through mentorship and code reviews. A key impact area is integrating AI capabilities—such as LLMs and RAG—into applications and engineering workflows to build smarter, faster, and more scalable solutions.

Responsibilities

  • Lead the technical design, development, and delivery of full-stack applications using Java/Spring Boot and modern frontend technologies
  • Define and drive application architecture, coding standards, design patterns, and engineering best practices
  • Provide technical direction and mentorship to developers through code reviews, design discussions, and technical guidance
  • Develop scalable and secure REST APIs, microservices, and backend services using Java and Spring Boot
  • Contribute to frontend development using technologies such as React, Angular, or similar frameworks
  • Drive the integration and adoption of AI capabilities into applications and engineering workflows
  • Design and implement solutions involving LLMs, Generative AI, AI APIs, RAG, embeddings, vector databases, or AI-assisted development tools, where applicable
  • Evaluate AI technologies, frameworks, and approaches and determine how they can be applied to business and technical requirements
  • Promote AI-first development practices, including the use of AI coding assistants for development, testing, documentation, and productivity
  • Troubleshoot complex technical issues across application, integration, and infrastructure layers
  • Collaborate with Product Managers, Business Analysts, QA, DevOps, and other stakeholders to translate requirements into technical solutions
  • Ensure applications meet standards for performance, scalability, security, reliability, and maintainability
  • Participate in technical discovery, estimation, proof-of-concepts, and architecture reviews
  • Stay current with emerging technologies in Java, cloud computing, full-stack development, and AI and identify opportunities for innovation

Required Qualifications

  • 6+ years of software development experience, with significant experience in Java
  • Strong hands-on experience with Java and Spring Boot
  • Solid understanding of microservices, REST APIs, database design, and enterprise application architecture
  • Strong full-stack development experience with at least one modern frontend framework (preferably React or Angular)
  • Experience leading technical projects, initiatives, or development teams
  • Strong understanding of software architecture, design patterns, clean code, and development best practices
  • Hands-on experience or demonstrated project exposure to AI/Generative AI technologies
  • Strong problem-solving, communication, and technical decision-making skills

Preferred Qualifications

  • Experience integrating AI/LLM APIs or AI capabilities into software applications
  • Experience with cloud platforms such as AWS, Azure, or GCP
  • Familiarity with CI/CD, Git, Docker, Kubernetes, and automated testing
  • Building applications using OpenAI, Azure OpenAI, Gemini, Claude, or other LLM APIs
  • Retrieval-Augmented Generation (RAG)
  • Vector databases and semantic search
  • Prompt engineering and LLM orchestration
  • AI agents and tool/function calling
  • Integrating AI into existing enterprise applications
  • AI-powered automation and workflow solutions
  • Using AI coding tools such as GitHub Copilot, Cursor, or Claude Code
  • Developing or modernizing applications using an AI-first engineering approach

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