Software Engineering Lead

Role & responsibilities

• Full-Stack Leadership: Architect, develop, and maintain secure, high-performance web applications utilizing Java (Spring Boot) and React.js
• Technical Governance: Drive code quality, technical design reviews, and engineering best practices across the full-stack lifecycle
• AI Integration: Lead the practical integration of Generative AI capabilities (e.g., LLM APIs, semantic search, or basic RAG workflows) into existing core applications to solve business problems
• API & Microservices Architecture: Design and optimize scalable RESTful microservices, ensuring robust data integrity and system performance
• Cloud & DevOps Collaboration: Partner with DevOps teams to deploy containerized applications via Docker into cloud environments (Azure/AWS), supporting CI/CD automation
• Mentorship & Delivery: Guide and mentor software engineers, break down complex requirements into technical tasks, and collaborate closely with Product Managers
• Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so

Preferred candidate profile

• Backend Mastery: Solid expertise in Java (7+) and the Spring Ecosystem (Spring Boot, Spring Security, Spring Data)
• Database Knowledge: Solid experience with relational databases (e.g., PostgreSQL or MySQL, COSMOS) and familiarity with caching strategies
• Modern DevOps Workflow: Experience working with Git, Docker, and standard CI/CD pipelines (GitHub Actions/Jenkins)
• AI Awareness & Practical Exposure: Familiarity with the Generative AI landscape, including consuming OpenAI/Anthropic APIs or utilizing AI orchestration frameworks (e.g., LangChain or Spring AI)
• Frontend Expertise: Advanced knowledge of modern React.js, TypeScript, state management (e.g., Redux/Context API), and responsive web design
• Modern DevOps Workflow: Experience working with Git, Docker, and standard CI/CD pipelines (GitHub Actions/Jenkins).

Preferred Qualifications:

• Experience migrating legacy systems to cloud-native microservices architectures
• Basic reading/writing familiarity with Python specifically for evaluating AI prototypes
• Familiarity with Vector Databases (e.g., Pinecone, Milvus, or pgvector)