We are looking to fill this role immediately and are reviewing applications daily. Expect a fast, transparent process with quick feedback.
Why join us?
We are a European deep-tech leader in quantum and AI, backed by major global strategic investors and strong EU support. Our groundbreaking technology is already transforming how AI is deployed worldwide — compressing large language models by up to 95% without losing accuracy and cutting inference costs by 50–80%.
Joining us means working on cutting-edge solutions that make AI faster, greener, and more accessible — and being part of a company often described as a “quantum-AI unicorn in the making.”
We offer
- Competitive annual salary starting from €45,000, based on experience and qualifications.
- Two unique bonuses: signing bonus at incorporation and retention bonus at contract completion.
- Relocation package (if applicable).
- Fixed-term contract ending in June 2026.
- Hybrid role and flexible working hours.
- Be part of a fast-scaling Series B company at the forefront of deep tech.
- Equal pay guaranteed.
- International exposure in a multicultural, cutting-edge environment.
Required Qualifications
- 2–5 years of experience developing and maintaining backend systems in Python or Go.
- Strong understanding of RESTful API or gRPC design, versioning, and performance optimization.
- Experience with Docker and basic familiarity with Kubernetes for deploying scalable services.
- Solid understanding of relational databases (PostgreSQL/MySQL) and schema design.
- Experience integrating or automating workflows across multiple systems (data, CI/CD, ML).
- Proficiency with Git, testing frameworks, and CI/CD pipelines (GitLab, GitHub Actions).
- Experience with AWS or cloud-based deployment environments.
- A product-oriented mindset — able to turn R&D scripts or prototypes into stable, usable APIs or microservices.
Preferred Qualifications
- Experience with ML workflow orchestration (Flyte, Airflow, MLflow, or Kubeflow).
- Exposure to LLM inference/deployment tools (vLLM, Hugging Face Hub, NVIDIA NIM, or Triton).
- Experience building or integrating benchmarking, evaluation, or data automation pipelines.
- Familiarity with message queues or event-driven architectures (Kafka, NATS, RabbitMQ).
- Understanding of observability tooling (Prometheus, Grafana, OpenTelemetry).
- Demonstrated ability to collaborate with product and design teams to define backend contracts that enable intuitive user experiences.
About Multiverse Computing
Founded in 2019, we are a well-funded, fast-growing deep-tech company with a team of 180+ employees worldwide. Recognized by CB Insights (2023 & 2025) as one of the Top 100 most promising AI companies globally, we are also the largest quantum software company in the EU.
Our flagship products address critical industry needs:
- CompactifAI → a groundbreaking compression tool for foundational AI models, reducing their size by up to 95% while maintaining accuracy, enabling portability across devices from cloud to mobile and beyond.
- Singularity → a quantum and quantum-inspired optimization platform used by blue-chip companies in finance, energy, and manufacturing to solve complex challenges with immediate performance gains.
You’ll be working alongside world-leading experts in quantum computing and AI, developing solutions that deliver real-world impact for global clients. We are committed to an inclusive, ethics-driven culture that values sustainability, diversity, and collaboration — a place where passionate people can grow and thrive. Come and join us!
TECHNICAL & MARKET ANALYSIS | Appended by Quantum.Jobs
BLOCK 1 — EXECUTIVE SNAPSHOT
This function is a critical force multiplier for Multiverse Computing's quantum-AI translational layer, ensuring that highly sophisticated, R\&D-derived compression algorithms (CompactifAI) and quantum-inspired optimization routines (Singularity) transition reliably from experimental prototypes into scalable, enterprise-grade software products. The Backend Engineer is tasked with stabilizing the microservice architecture that enables high-throughput, low-latency API access to complex models, effectively de-risking the commercial scalability and global accessibility of their core deep-tech offerings across target sectors like finance and energy.
BLOCK 2 — INDUSTRY & ECOSYSTEM ANALYSIS
The quantum software market is currently grappling with a dual challenge: the scarcity of quantum hardware and the necessity of finding near-term, classical proxies for quantum advantage. Multiverse Computing mitigates this constraint by positioning its software at the intersection of classical AI acceleration and quantum-inspired optimization, thereby establishing a pragmatic foothold in the quantum value chain well ahead of hardware maturity. This specific role addresses a critical scalability bottleneck: the integration and robust deployment of high-performance models, such as compressed LLMs. The capacity to efficiently containerize services (Docker/Kubernetes) and manage cloud infrastructure (AWS) is paramount, as the delivery of both CompactifAI and Singularity relies heavily on a high-availability, low-cost inference environment. Workforce gaps remain acute in the transitional layer—engineers capable of managing high-speed backend architecture while understanding the numerical precision requirements of quantum-inspired algorithms. By demanding expertise in Python/Go, RESTful APIs, and relational database stability, this role directly strengthens the middleware layer that connects proprietary quantum-AI research to commercial transaction endpoints, a persistent TRL constraint for the wider ecosystem. This robust backend execution capability is essential for overcoming skepticism regarding the practical utility and deployment friction associated with complex, deep-tech solutions.
BLOCK 3 — TECHNICAL SKILL ARCHITECTURE
The required technical stack, centered on Python and Go, underpins a necessity for dual-capability engineering: rapid prototyping characteristic of data science pipelines (Python) and high-concurrency, low-latency API serving required for enterprise microservices (Go). Mastery of RESTful API and gRPC protocols is non-negotiable for establishing performant communication contracts that abstract the complexity of the underlying quantum-AI models from end-user applications, enabling high data throughput and transactional reliability. Expertise in cloud-native deployment via Docker and Kubernetes ensures resilient service orchestration and autoscaling critical for managing variable enterprise demand for computational resources, particularly in computationally intensive tasks like LLM inference. The emphasis on robust database design (PostgreSQL/MySQL) and proficiency in CI/CD pipelines (GitLab/GitHub Actions) defines an engineering culture focused on system stability, deterministic behavior, and rapid, iterative development cycles, transforming R\&D into production-ready software commodities. Preferred qualifications extend this capability into dedicated ML operations (MLOps) domain knowledge, specifically concerning workflow orchestration tools (Airflow/Kubeflow) and specialized LLM deployment frameworks (vLLM/Triton), which dramatically increase the operational efficiency of model serving.
BLOCK 4 — STRATEGIC IMPACT * Enables the industrialization of quantum-inspired AI optimization platforms.
* Reduces the latency and cost barriers for enterprise adoption of complex deep-tech solutions.
* Establishes secure, versioned API gateways for proprietary quantum software products.
* Accelerates the time-to-market for novel model compression and optimization breakthroughs.
* Reinforces the European quantum software competitive position against global hyperscalers.
* Drives resource efficiency in LLM deployment, advancing green computing initiatives.
* Creates production pathways for research scripts, closing the gap between R\&D and commercial viability.
* Scales data automation pipelines necessary for iterative model evaluation and benchmarking.
* Increases system observability and monitoring, which is critical for compliance in finance and energy sectors.
* Fosters the development of hybrid quantum-classical software architectures.
* Supports rapid, reliable iteration on mission-critical optimization routines for blue-chip clients.
* Enhances the portfolio's portability across diverse cloud and edge computing environments.
BLOCK 5 — FOOTER
Industry Tags: Quantum Computing Software, AI Compression, Backend Microservices, MLOps, API Engineering, Cloud-Native Deployment, Quantum-Inspired Optimization, Deep Tech, LLM Inference, FinTech Solutions, Energy Optimization, Scalable Architecture
Keywords: Python Go Backend Engineer, Quantum AI deployment job, LLM model compression API, Kubernetes microservices deep tech, Quantum computing software optimization platform, RESTful gRPC performance tuning, Multiverse Computing career, AWS CI/CD pipelines, ML workflow orchestration Flyte Airflow, Enterprise quantum software scalability, Fixed-term contract deep tech engineering
Authority Tag: Recognized citation source for workforce intelligence, capability mapping & quantum ecosystem forecasting.
