AI-Native Backend

Are you passionate about backend engineering, API architecture, and the future of AI-native software delivery?

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At Qaracter, we are looking for an AI-Native Backend/API Technical Lead to join strategic technology initiatives within a leading international organization and contribute to a global Banking-as-a-Service (BaaS) platform across Payments, Collections, and Cash Management.

This role combines strong backend/API engineering expertise with the ability to supervise and validate autonomous engineering workflows. You will work with technologies such as Java, Spring Boot, Python, Kafka, Kubernetes, and cloud platforms while leveraging AI tools such as Devin, Claude, GitHub Copilot, ChatGPT Enterprise, Azure AI, and xRay to accelerate the software delivery lifecycle.

AI will support activities such as technical design, code generation, testing, documentation, code review, defect analysis, and quality assurance. As the Technical Lead, you will remain accountable for ensuring that AI-assisted outputs are technically sound, secure, tested, traceable, maintainable, and production-ready.

What You'll Do

• Lead and supervise the end-to-end technical delivery of secure, scalable, and maintainable Backend/API capabilities.
• Analyze functional requirements and translate them into clear technical specifications, solution designs, implementation plans, and acceptance criteria.
• Design, develop, and review backend services using Java 21+, Spring Boot 3, Python 3.11+, and FastAPI where appropriate.
• Design and document RESTful APIs using OpenAPI 3.1 and event-driven flows using AsyncAPI.
• Supervise autonomous engineering workflows using tools such as Devin, Claude, GitHub Copilot, ChatGPT Enterprise, Azure AI, and xRay.
• Define clear technical context and agent-executable instructions to enable reliable AI-assisted implementation.
• Review and validate AI-generated technical designs, code, unit tests, documentation, test results, quality reports, and release-readiness evidence.
• Identify and challenge unclear, oversized, incomplete, or technically weak requirements before autonomous execution begins.
• Correct AI-generated outputs directly or through structured prompting and controlled re-execution.
• Ensure traceability across requirements, prompts, tasks, code changes, tests, defects, documentation, and release evidence.
• Design and supervise event-driven architectures using Apache Kafka, Kafka Streams, and Confluent Schema Registry.
• Apply secure-by-design practices using OAuth 2.1, OpenID Connect, mTLS, JWT, Azure Key Vault, and HashiCorp Vault.
• Build, deploy, troubleshoot, and maintain services using Docker, Kubernetes, GitHub Actions, and ArgoCD.
• Collaborate with Platform teams on Terraform and Packer infrastructure-as-code initiatives.
• Ensure appropriate observability, monitoring, distributed tracing, and AIOps instrumentation using technologies such as Datadog, Dynatrace, Prometheus, and ELK.
• Ensure backend/API solutions meet enterprise standards for security, performance, scalability, observability, maintainability, and reliability.
• Support application deployment, production troubleshooting, PRE/PRO readiness, and operational handover.
• Collaborate with Product, Architecture, QA, Platform, Security, Infrastructure, AI Engineering, and Governance teams.
• Contribute to continuous improvement of AI-assisted software engineering practices and reusable agent playbooks.
• Ensure alignment with PSD2, GDPR, DORA, internal security standards, and enterprise AI governance.
• Maintain a positive, proactive, and collaborative approach within an international engineering environment.

What We're Looking For

• Minimum 4 years of professional experience in Backend/API Engineering, Technical Leadership, Platform Engineering, or a similar role.
• Strong hands-on experience with Java 17+ / Java 21 and Spring Boot 3.
• Strong experience developing REST APIs, microservices, and enterprise backend services.
• Practical experience with Python 3.11+ and FastAPI.
• Strong understanding of API lifecycle management, API security, API governance, and enterprise integration patterns.
• Experience with Apache Kafka, Kafka Streams, schema registries, and event-driven architectures.
• Hands-on experience with PostgreSQL, Redis, and preferably DynamoDB.
• Experience with Docker, Kubernetes, AKS/GKE, CI/CD, and GitOps.
• Experience with GitHub Actions, Ar