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

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, ArgoCD, Terraform , and preferably Packer.
Knowledge of API Management platforms such as Apigee Hybrid and/or Azure API Management .
Strong understanding of OAuth 2.1, OIDC, JWT, mTLS , and enterprise secrets management.
Experience with observability, monitoring, distributed tracing, AIOps, and static analysis.
Experience with automated testing, code quality, security scanning, defect analysis, and release-readiness processes.
Experience supervising, reviewing, or quality-assuring AI-assisted software engineering outputs .
Comfortable working with autonomous engineering tools such as Devin, Claude, GitHub Copilot, ChatGPT Enterprise, Azure AI, or similar .
Ability to create clear technical instructions, prompts, implementation context, acceptance criteria, and validation criteria for AI-assisted workflows.
Experience working in Payments, Banking-as-a-Service, Collections, Cash Management, or financial services is strongly preferred.
Experience working in regulated environments with GDPR, PSD2, DORA , or equivalent frameworks.
Strong analytical and problem-solving skills, with the ability to identify weaknesses in AI-generated designs, code, tests, and documentation.
Strong communication and collaboration skills.
English and Spanish: professional working proficiency.

⭐ Nice to Have

Experience with RAG architectures, vector databases, semantic caching, LangChain, LangGraph, or equivalent frameworks .
Experience with LLMOps, prompt engineering, AI-assisted SDLC, and enterprise AI governance .
Experience with Confluent Platform and schema evolution governance .
Experience with service mesh technologies such as Istio or Linkerd .
Experience with automated code review, AI-generated testing, test result validation, and defect triage.
Experience creating reusable AI agent playbooks, prompt-driven automations, and scheduled agent workflows .
Experience supporting PRE/PRO readiness, production deployment, and operational handover .
Experience mentoring engineers in AI-assisted development practices .
Experience working with large-scale enterprise or international technology environments.
Experience within Agile/Scrum engineering teams.

What We Offer

Opportunity to work on challenging Backend/API and AI-native engineering initiatives with high business impact.
Opportunity to contribute to a global BaaS platform across Payments, Collections, and Cash Management.
Exposure to modern backend technologies, cloud platforms, event-driven architectures, and autonomous engineering tools.
Opportunity to shape and improve AI-assisted software delivery practices within an enterprise environment.
Collaborative and international engineering environment.
Long-term project opportunities with continuous learning and professional development.
Remote work opportunity from Spain.
Competitive compensation package.

About Qaracter

Qaracter is an international consulting firm providing business, financial, risk, technology, and operations advisory services. We combine deep industry knowledge with hands-on execution to deliver real impact.

With presence in Spain, Argentina, Mexico, Brazil, and the United States, and activity across Europe and the UK, we partner with top-tier organizations on complex transformation initiatives.

Equal Opportunity Statement

At QARACTER Group, we are committed to ensuring equal opportunities and non-discrimination in all our processes, promoting an inclusive and diverse work environment. All applications are welcome regardless of sex, gender, gender identity or expression, sexual orientation, origin, ethnicity, age, disability, or any other personal or social condition, in line with our Equal Opportunity Plan and our commitment to equity.

AI-Native Backend

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