LLM Inference Platform Architect
At a glance
Mid-level ML Platform & Ops role at Qutwo. Helsinki · full-time.
Pay not stated ML Platform & Ops salary
aimlroles summary, based on the employer's posting.
What you'll do
- Design and lead a private LLM service on GPU hardware the organization controls, keeping data in-house
- Run the serving stack, from GPU clusters and inference engines to access controls and capacity planning
- Set platform standards and maintain regulatory compliance, including DORA
- Coordinate with security, operations and LLM scientists to deploy optimized models
What you bring
- You have designed and operated large infrastructure on Kubernetes, including GPU-based workloads
- You have hands-on experience with LLM serving engines such as vLLM, SGLang or another listed option
- You can use infrastructure-as-code approaches such as Terraform, plus CI/CD and observability tools
- You understand enterprise security, identity and network architecture, and have written architecture guidance with enterprise architecture teams
Who this fits
This mid-level role suits an infrastructure architect focused on secure, internally hosted LLM serving. The work covers platform leadership and hands-on coordination with security, operations and LLM science teams. The role is based in Helsinki, Finland.
From the employer
Join QuTwo - Europe's private Quantum AI Lab, on our quest to bridge the gap between the classical and the quantum world. We partner with the most advanced and forward-thinking customers, solving fundamental real-world problems, side by side.
We are a European AI lab for the quantum era, co-founded by pioneers behind IQM and Silo AI, with a team spanning MIT, UC Berkeley, Cambridge, and Carnegie Mellon, and backed by the founders of Skype, Hugging Face, Quantinuum, Supercell and many more. We work at the intersection of quantum computing, AI, optimization, and simulation — where the answers do not yet exist and the work genuinely matters.
We are seeking LLM Inference Platform Architect. If you are a humble learner, not afraid of the unknown, we encourage you to apply.
Role Description
The Infrastructure Architect designs and leads a secure, internal LLM serving platform on fully controlled GPU hardware, ensuring complete data privacy and independence from external model providers.
Managing the full serving stack—including GPU clusters, inference engines, access control, and capacity planning—this role delivers a reliable AI service for the entire organization. The architect sets platform standards, ensures strict regulatory compliance (such as DORA), and partners closely with security, operations, and LLM scientists to deploy optimized models.
Qualifications
Experience designing and running large-scale infrastructure on Kubernetes, including GPU workloads
Hands-on experience with LLM inference engines (vLLM, SGLang, TensorRT-LLM or similar)
Infrastructure as code (Terraform or similar), CI/CD and observability tooling
Understanding of security, identity and network design in enterprise environments
Experience writing architecture guidelines and working with enterprise architecture teams
Experience in one or more of the following areas is a plus but not a requirement:
Hands-on experience configuring and managing enterprise-grade GPUs (NVIDIA or AMD Instinct) and their respective acceleration stacks (CUDA or ROCm).
Background in banking or other highly regulated industries, with familiarity with DORA or equivalent compliance frameworks.
ML Platform & Ops work from LinkedIn, X, Reddit and Upwork, in one list.
Each morning you get everything that fits, strongest first.
ML Platform & Ops
Find me workBy the team behind aimlroles.