> Markdown version of [/jobs/ext/4211140-lead-senior-backend-engineer](https://www.wearedevelopers.com/jobs/ext/4211140-lead-senior-backend-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Lead Senior Backend Engineer - **Company:** T-mobile - **Location:** A Coruña, Spain - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Application Integration Architecture, User Authentication, Microsoft Azure, C++ (Programming Language), Cloud Computing, Profiling, Software Quality, Code Review, Continuous Integration, Information Engineering, Database Design, DevOps, Distributed Systems, Django Web Framework, Fault Tolerance, Identity and Access Management, Interoperability, Python (Programming Language), Key Management, Load Testing, OAuth, Performance Tuning, Queueing Systems, Role-Based Access Control, Prometheus, JSON Web Token, Software Engineering, SQL Databases, Web Application Frameworks, WebSocket, AI Infrastructure, Rust (Programming Language), Data Logging, Data Processing, Real Time Systems, Retrieval-Augmented Generation, Flask (Web Framework), Delivery Pipeline, Large Language Models, Grafana, Generative AI, Backend, Rate Limiting, Fastapi, Event Driven Architecture, Build Management, Containerization, Kubernetes, Information Technology, Low Latency, SGLang, Build Tools, Machine Learning Operations, Front End Software Development, TensorRT, Asynchronous Programming, Api Design, Api Gateway, Restful APIs, VLLM, Model Inference, Grpc, Webhooks, Data Pipelines, Dynatrace, Api Management, Docker, Microservices - **Published:** October 16, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=a08d55e1849e56d0 ## About the Role We are looking for a senior backend engineer with strong system design skills and experience building production infrastructure. This role involves architecting and maintaining backend platform services behind AI inference endpoints - a multi-tenant system handling authentication, API key management, usage metering, billing and request proxy. This is a high-ownership role where you will shape architecture decisions, raise the bar of engineering quality and build systems that are performant, secure and observable at scale. You'll collaborate with experts in AI infrastructure and data engineering to build robust, secure, and efficient systems that scale to millions of requests., We are seeking a Senior Backend Engineer / Python Developer with extensive experience in building and operating production backend systems at scale, strong system design skills, and deep expertise in distributed systems and API development. The ideal candidate will have proven experience with authentication systems, cloud infrastructure, and modern Python development., * Degree in Computer Science, Software Engineering, or equivalent professional experience * 5+ years of experience building and operating backend systems in production with meaningful scale * 5+ years of experience developing backend systems with a focus on API design and high-scale production environments * Strong proficiency in Python with deep knowledge of asynchronous programming, modern Python tooling and profiling * Proficiency in at least one systems-oriented language (Go, Rust, Java, C++) * Willingness to work across the current stack which includes Python (FastAPI) * Proven experience designing and maintaining REST APIs in production environments * Experience with REST, gRPC, WebSockets, and SSE protocols and understanding of the tradeoffs between them * Experience with websockets, SSE, and Webhooks * Solid understanding of distributed systems including consistency, fault tolerance, concurrency, performance and networking * Solid understanding of data pipelines and performance optimization * Experience designing authentication and authorization systems (OAuth2, JWT, API key management, RBAC/ABAC) * Experience with cloud infrastructure (AWS, GCP, or Azure) * Experience with containerized environments (Docker) * Experience with container orchestration (Kubernetes) * Understanding of database design (SQL, ORMs etc.) and data modeling at scale * Fluent in English (written and verbal) * Comfortable collaborating in international teams, * Experience with high-throughput, low-latency or real-time systems (e.g., message queues, event-driven architectures) * Familiarity with generative AI or large language models (e.g., integration of AI APIs, RAG workflows, or vector databases) * Knowledge of modern DevOps practices * Experience with infrastructure as code * Knowledge of GitOps workflows * Experience with observability tools (Prometheus, Grafana, OpenTelemetry) * Exposure to ML serving infrastructure (model servers, GPU scheduling, inference optimization) * Comfortable occasionally touching or contributing to frontend code when necessary * Experience in stress/load-testing and evaluating performance of production systems * Strong problem-solving mindset and commitment to code quality and performance excellence * Track record of improving engineering culture: mentoring junior engineers, introducing better practices, leading technical discussions ## Description * Design and build core platform services: API gateway, authentication, authorization, key rotation, and multi-tenant isolation * Design, implement, and optimize APIs and backend systems using Python frameworks such as primarily FastAPI (or Flask, or Django) * Architect and implement usage metering, billing integration, and rate limiting for inference endpoints * Build and maintain scalable, fault-tolerant microservices for data processing and AI integration * Build and operate a high-throughput proxy/routing layer for AI model serving traffic * Collaborate with cross-functional teams to design system architecture and ensure seamless system interoperability * Design telemetry and observability into the platform from the ground up - structured logging, distributed tracing, metrics, and alerting * Implement robust CI/CD pipelines, monitoring, and observability for high-performance production systems * Drive technical decisions on architecture, data modeling, and technology choices * Identify performance bottlenecks and drive improvements in reliability, scalability, and latency * Establish engineering standards for the backend codebase: testing, code review, CI/CD, and deployment practices * Ensure best practices for security, compliance, and maintainability across the API lifecycle * Collaborate closely with the ML infrastructure team to integrate with model serving systems (e.g., NVIDIA Dynamo, vLLM, SGlang, TensorRT-LLM), * Customized training: access to Coursera to learn whatever you want, whenever you want * Weekly language classes (English, Spanish & German) * International Mentoring Sessions & Experience Days