Jobs at Qutwo

Designs and leads a secure internal LLM serving platform on controlled GPU infrastructure. Responsibilities include managing GPU clusters, inference engines, access control, capacity planning, platform standards, regulatory compliance, and optimized model deployment. The role collaborates with security, operations, enterprise architecture, and LLM science teams to deliver reliable, private AI services.

Owns enterprise business development across Finland and Sweden, managing complex AI, software, and infrastructure deals from prospecting through close. Responsibilities include building executive relationships, closing seven-figure partnerships, translating customer needs into R&D scopes, managing pipeline and forecasts, and supporting market expansion. The role requires strong enterprise sales performance, technical fluency, C-level engagement, and established relationships within life sciences, material sciences, autonomous systems, or financial services.

Own enterprise business development for QuTwo’s expansion into the French or German market. Responsibilities include prospecting, targeting, account planning, managing complex multi-quarter deals, engaging C-suite sponsors, shaping AI partnership scopes with strategists and R&D teams, closing seven-figure agreements, forecasting pipeline, and contributing to the company’s sales playbook.

Open application for researchers, scientists, engineers, customer deployment specialists, business leaders, and company operators at a European AI lab working across AI, quantum computing, optimization, and simulation. Candidates should demonstrate depth in their discipline, ownership from idea to outcome, strong communication, and comfort with ambiguity. Experience with enterprise customers, regulated industries, hybrid AI systems, or scaling startups is advantageous.

Design, build, secure, and operate GPU and HPC data center infrastructure. Responsibilities include rack and power design, cooling, cabling, high-performance networking, storage, provisioning, firmware and driver management, monitoring, scheduling, security controls, compliance, capacity planning, and operational troubleshooting.

Build and lead Qutwo’s first in-house legal function, covering commercial contracts, corporate and venture financing, privacy, EU AI Act readiness, employment and IP, M&A, disputes, external counsel, and legal operations. Develop an AI-enabled legal function using legal technology, automation, reusable workflows, and self-service tools. The role partners with business teams across international markets and is preferably based in Helsinki.

Build and operate a secure, portable, multi-cloud Kubernetes platform for ML workloads and SaaS services. Responsibilities include infrastructure design, observability, SLOs, incident practices, infrastructure as code, GitOps, Ray workload scheduling, autoscaling, cost optimization, security controls, and CI/CD enablement. The role also establishes reliability foundations, troubleshoots distributed systems, documents architectural decisions, and supports engineering teams using AI-assisted development tools.

Design, deploy, and maintain production-grade LLM architectures and autonomous agentic AI systems. Collaborate with scientists, engineers, and customers to solve complex problems, lead cross-functional technical initiatives, translate business goals into roadmaps, and promote reliable, observable, safe, high-quality engineering. Mentor teams, conduct architecture and code reviews, and advance systems involving RAG, fine-tuning, agent memory, evaluation, vector databases, distributed computing, GPU optimization, and quantum computing.

Lead and coordinate multi-quarter enterprise design partnerships, translating strategic customer ambitions into executable technical scope, driving deployments, customer success, expansion, and codifying playbooks across BD, R&D, product, and client teams.

Build and operate cloud and ML infrastructure: maintain CI/CD pipelines, IaC, Kubernetes/Docker environments, observability (Prometheus/Grafana/OpenTelemetry), and support ML model deployment and platform reliability for engineering and research teams.

Conduct applied and exploratory AI research; build end-to-end ML solutions with scientists, engineers, and customers; translate complex problems into mathematical models; mentor junior researchers and deliver high-impact, scalable ML implementations for quantum-era applications.