Platform Engineer
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Job Summary
Multiverse Computing
Multiverse is a well-funded fast-growing deep-tech company founded in 2019. We are the largest quantum software company in the EU and have been recognized by CB Insights (2023 and 2025) as one of the 100 most promising AI companies in the world.
With 180 employees and growing our team is fully multicultural and international. We deliver hyper-efficient software for companies seeking a competitive edge through quantum computing and artificial intelligence.
Our flagship products CompactifAI and Singularity address critical needs across various industries:
CompactifAI is a groundbreaking compression tool for foundational AI models based on Tensor Networks. It enables the compression of large AI systemssuch as language modelsto make them significantly more efficient and portable.
Singularity is a quantum- and quantum-inspired optimization platform used by blue-chip companies to solve complex problems in finance energy manufacturing and beyond. It integrates seamlessly with existing systems and delivers immediate performance gains on classical and quantum hardware.
Youll be working alongside world-leading experts to develop solutions that tackle real-world challenges. Were looking for passionate individuals eager to grow in an ethics-driven environment that values sustainability and diversity.
Were committed to building a truly inclusive culturecome and join us.
About the role
Foundry is a sovereign AI development platform. It works by incorporating industry leading model optimization algorithms with best-in-class open-source engines behind one UI API and identity layer and it has to run wherever our customers need: public cloud private and sovereign cloud on-premises Kubernetes and air-gapped environments.
You will own how Foundry gets deployed and how it connects to the world around it. On the infrastructure side that is the packaging installation and upgrade path of the platform across every environment we support and the integration with customer infrastructure (identity storage registries networking GPU scheduling). On the backend side it is the Third-Party Apps module: a Python service and API through which external open-source applications are packaged installed configured and managed as first-class apps inside Foundry with proper identity configuration and observability. This is a hands-on role; you will write production Python and production Helm and you will be the person who knows why a deployment works.
You will work within Platform Engineering alongside the owners of the metadata catalog and IAM modules and with the teams building Foundrys compression fine-tuning serving and orchestration capabilities.
Responsibilities
Design build and maintain the Python services through which external applications engines and infrastructure are integrated and managed inside Foundry: manifest schemas and validation catalogs and versioning install/upgrade/remove lifecycles configuration and secrets handling health reporting and the REST APIs that expose them to the Foundry UI and CLI.
Define the integration contract that lets an external engine plug into Foundrys IAM metadata layer and UI once and drive the first integrations through it.
Own Foundrys deployment packaging (Helm charts operators offline bundles) and keep the platform installable upgradable and supportable across Kubernetes distributions cloud providers sovereign clouds and air-gapped environments.
Integrate Foundry with customer-side infrastructure: OIDC/SAML identity providers object storage container registries ingress and network policy and GPU scheduling.
Own the CI/CD pipelines release process and multi-environment integration test matrix that validate every supported deployment target.
Instrument the platform and installed apps with metrics logs and traces and write the runbooks needed to operate and support production deployments.
Turn prototypes and one-off integrations into stable documented versioned services and tooling that other teams and customers can rely on.
Required Qualifications
5 years in platform infrastructure or backend engineering with at least 2 years shipping and operating production workloads on Kubernetes.
3 years writing production Python: you have owned backend services end to end including API design data models testing and packaging not only automation scripts.
Experience building and maintaining REST APIs in a modern Python framework (FastAPI Django REST Framework or similar) including versioning authentication and input validation (Pydantic or equivalent).
Experience with Python data access and migrations (SQLAlchemy Alembic or equivalent) on PostgreSQL and with schema design.
Comfortable with async Python structured logging and writing testable code with Pytest; you use type hints and linters as a matter of course.
Experience interacting with Kubernetes and cloud APIs programmatically from Python (Kubernetes client Boto3 or equivalent) for example building installers controllers or operational tooling.
Deep hands-on experience with Helm and Kubernetes packaging; you have written and maintained charts that other people install.
Experience deploying software into environments you do not control: on-premises private cloud or restricted-network/air-gapped installs.
Experience with AWS: EKS ECR RDS S3 Secrets Manager.
Experience integrating with enterprise identity (OIDC OAuth2 SAML) and managing secrets and configuration in production.
Solid understanding of Docker image building and hardening and container registries.
Proficiency with Git and CI/CD pipelines (GitLab CI or GitHub Actions).
A product-oriented mindset: able to turn R&D scripts or prototypes into stable usable services.
Preferred Qualifications
Experience writing Kubernetes operators or controllers (in Python with kopf or in Go) or with GitOps tooling (ArgoCD Flux).
Experience building plugin extension or app-store style systems: manifest formats lifecycle hooks dependency and version resolution.
Experience publishing Python packages or CLIs that others install (packaging versioning backwards compatibility).
Experience with GPU workloads on Kubernetes (device plugins node scheduling NVIDIA GPU Operator) and with LLM serving tools (vLLM Triton NIM).
Familiarity with observability tooling (Prometheus Grafana OpenTelemetry) and with exposing it for third-party components.
Exposure to ML orchestration tooling (Flyte Airflow MLflow SkyPilot).
Go and a track record of contributing to open-source infrastructure projects.
Perks & BenefitsIndefinite contract.
Equal pay guaranteed.
Variable performance bonus.
Signing bonus.
We offer work visa sponsorship (If applicable).
Relocation package (if applicable).
Private health insurance.
Flexible remuneration: hospitality and public transportation.
Eligibility for educational budget according to internal policy.
Hybrid opportunity.
Flexible working hours.
Language classes and discounted lunch options
Working in a high paced environment working on cutting edge technologies.
Career plan. Opportunity to learn and teach.
Progressive Company. Happy people culture
As an equal opportunity employer Multiverse Computing is committed to building an inclusive workplace. The company welcomes people from all different backgrounds including age citizenship ethnic and racial origins gender identities individuals with disabilities marital status religions and ideologies and sexual orientations to apply.
