Additionalinformation

Additional Information

What do we offer you?

Work environment & flexibility

• International, dynamic and collaborative environment
• T-Social: social initiatives (sports, community, health, ...)
• Hybrid work model (remote/on-site)
• Flexible working hours

Growth & development

• Customized training: access to Coursera to learn whatever you want, whenever you want
• Weekly language classes (English, Spanish & German)
• International Mentoring Sessions & Experience Days

Compensation & benefits

• Flexible compensation plan (health insurance, meal vouchers, childcare, transport)
• Telemedicine
• Life and accident insurance
• Social fund

Wellbeing & time off

• 26+ working days of vacation per year
• Free access to specialist services (medical, legal, wellness)
• 100% salary coverage during medical leave

And many more advantages of being part of T-Systems! If you are looking for a new challenge, do not hesitate to send us your CV! Please send CV in English. Join our team! T-Systems Iberia will only process the CVs of candidates who meet the requirements specified for each offer.

Companydescription

Company Description

T‑Systems is part of the Deutsche Telekom Group, with around 30.000 employees worldwide. We create technology with purpose to generate a positive impact on society. We are looking for curious talent, eager to learn, take on challenges, and contribute ideas that transform our customers’ experience.

We trust people: we offer autonomy, continuous support, and a collaborative environment where you can grow without limits. We are one global team, guided by respect, integrity, and a passion for doing better every day.

Jobdescription

Job Description

T-Systems is at the forefront of innovation, delivering advanced technology solutions across sectors including automotive, healthcare, and public services. Our AI Foundation Services team builds the platform infrastructure that powers AI inference at scale, including API gateways, authentication, billing, and multi-tenant serving.designs and builds high-performance backend systems and APIs that power intelligent applications across diverse industries. We cultivate a collaborative engineering culture where technical depthcreativity and ownership technical expertise drive real-world impact.

Role Overview

As a Lead AI Platform Engineer, you will design, build, and operate a scalable, production-grade platform for deploying and running autonomous AI agents, including model serving, tool-calling, and state management.

You will develop high-performance, low-latency inference services on GPU/TPU clusters, implement autoscaling with Kubernetes and Knative, and build CI/CD and MLOps pipelines for model versioning, canary releases, and rollback.

You will also contribute to platform reliability, observability, and security, while developing tools that enable internal teams and external partners to efficiently integrate with and use the AI platform. The role combines software engineering, distributed systems, and AI infrastructure, with a strong focus on delivering secure, scalable, and reliable production solutions.

Responsibilities and Duties

• Design and own the core platform that builds, deploys, and runs autonomous AI agents (model serving, tool‑calling, state management).
• Build high‑throughput, low‑latency inference services on GPU/TPU clusters and implement autoscaling with Kubernetes/Knative.
• Create CI/CD & MLOps pipelines for model versioning, canary releases, and rollback.
• Define SLO/SLI, set up monitoring (Prometheus, OpenTelemetry), and lead incident response.
• Implement security controls (IAM, sandboxed execution, data‑residency policies).
• Deliver developer‑friendly SDKs, CLI tools, and documentation for internal teams and external partners.
• Mentor junior engineers and champion best‑practice code standards.

Qualifications

Must-have requirements:

• 7+ years software engineering; 4+ years building large‑scale distributed systems.
• Proficient in Go or Rust and Python; strong Kubernetes, Docker, Helm experience.
• Hands‑on with model serving frameworks (Triton, vLLM, TensorFlow Serving) and GPU/TPU workloads.
• Experience with event streaming (Kafka/Pulsar) and infrastructure‑as‑code (Terraform/Pulumi).
• Solid knowledge of LLM concepts, retrieval‑augmented generation, and tool‑use APIs.
• Strong debugging, observability (Prometheus, Grafana, OpenTelemetry), and security (IAM, Vault) skills.
• Excellent communication and a bias toward shipping reliable, production‑grade code.

Nice-to-have requirements:

• Ph.D./M.S. in CS or related field.
• Experience with serverless runtimes, vector DBs (FAISS, Milvus), or agent frameworks (LangChain, AutoGPT).
• Open‑source contributions in AI/ML infrastructure.

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