You will lead backend development efforts for Ozone’s Open Finance platform while exploring opportunities to leverage Large Language Models (LLMs), intelligent automation, and data-driven insights to enhance platform intelligence, developer experience, and customer value.

This role is ideal for a hands-on technical leader who can design complex systems, guide engineers, and help shape Ozone’s AI-driven backend roadmap.

Key Responsibilities

• Lead the design, development, and maintenance of core backend components that power the Ozone API platform.
• Architect and implement scalable, secure, and resilient APIs aligned with global Open Banking and Open Finance standards.
• Identify and embed AI capabilities within backend services — such as intelligent data enrichment, anomaly detection, adaptive routing, or context-aware API responses.
• Collaborate with product and AI/Tools teams to design AI-enabled microservices, connectors, and orchestration flows.
• Design and lead proof-of-concept implementations for AI-powered features
• Implement clean, testable, and maintainable code with an emphasis on reliability, performance, and observability.
• Mentor and guide engineers on backend design principles, AI integration, and best practices in modern backend architecture.
• Participate in architecture reviews and technical design discussions across teams.
• Work closely with DevOps and Tools Engineers to ensure smooth CI/CD, deployment, and monitoring of AI-integrated components.
• Contribute to continuous improvement of Ozone’s backend engineering and AI adoption frameworks.

Skills & experience

• 10+ years of experience in product development.
• Must have experience in Typescript and NodeJS ecosystem , and the ability to adapt to new technologies quickly.
• Strong understanding of version control and GitOps practices.
• Proven experience with CI/CD tools and modern deployment pipelines.
• Familiarity with containerisation principles (Docker, Kubernetes) and related tools.
• Exposure to AI concepts and hands-on experience with AI/LLM-based integrations, APIs, or agent frameworks.
• Understanding of AI engineering concepts such as prompt design, embeddings, retrieval-augmented generation (RAG), and vector databases is desirable.
• Experience working in an agile environment and strong understanding of DevOps and automation principles.
• Strong analytical and problem-solving skills, capable of handling complex projects independently.
• Excellent communication and collaboration skills across technical and non-technical teams.

Preferred AI Exposure

• Experience with any of the following would be an added advantage:
• Experience with n8n, GitHub Copilot, Claude Code, or similar AI-assisted development tools.
• Understanding of AI observability, MLOps, or data pipeline automation.
• Familiarity with cloud-based AI services (AWS Bedrock, Azure OpenAI, GCP Vertex AI, etc.).

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