Responsibilities
- Design, develop, and maintain high-performance, scalable Java-based enterprise applications
- Build and enhance backend services, APIs, and microservices architecture
- Write clean, efficient, and maintainable code following best practices and coding standards
- Troubleshoot, debug, and optimize application performance and reliability
- Ensure application security, scalability, and high availability
- Support continuous integration and deployment processes
- Participate in architecture discussions and contribute to technical design decisions
- Lead a small AI team to design and deliver AI-powered features within our core platform
- Integrate AI/ML capabilities — such as automated reporting, anomaly detection, smart alerts, and incident workflows — into existing Java-based services
- Evaluate and adopt emerging AI tools and frameworks (e.g. LLMs, RAG, Agentic AI) where they add practical value to the product
- Ensure AI solutions are production-grade: secure, explainable, performant, and aligned with business goals
- Act as a bridge between AI experimentation and core product engineering — keeping AI grounded in real product impact
- Collaborate closely with Product Management, Engineering, QA, and DevOps teams, including remote teams
- Conduct code reviews and mentor junior developers
- Contribute to a culture of technical excellence, speed, and ownership
Requirements
- 10+ years of experience in software development for enterprise applications
- Strong proficiency in Java, Spring Boot, and Microservices architecture
- Hands-on experience with Apache Kafka for building scalable, real-time data pipelines and event-driven microservices
- Experience building RESTful APIs and distributed systems
- Good understanding of databases (SQL/NoSQL) and data modelling concepts
- Strong understanding of software design patterns and system architecture
- Experience working in Agile development environments
- Demonstrated ability to lead small technical teams or work streams
- Strong analytical, problem-solving, and communication skills
- Ability to collaborate effectively with cross-functional and distributed teams
Nice to Have
- Practical experience integrating AI/ML models or services into production Java applications
- Familiarity with Python and AI/ML frameworks (TensorFlow, PyTorch, or equivalent)
- Understanding of LLM integrations, RAG pipelines, or agent-based AI systems
- Exposure to AI system design and scalable AI architectures
Additional Information
- Willingness to work alternate Saturdays
- Comfortable with dynamic workloads and flexible work hours, typical of a startup environment
- Speed, adaptability, and ownership mindset are essential
