Jobs at Disseqt AI

Own and execute GTM with Global System Integrators in the UK/Europe: open senior GSI doors, generate partner-sourced pipeline, co-sell into regulated enterprise accounts, close net-new logos, and protect/expand commercial relationships post-deployment.

Lead EMEA pre-sales technical lifecycle for AI assurance, architect multi-model enterprise AI solutions, engage GSIs and regulated clients, translate requirements to product/engineering, run customer deep-dives, and build the regional pre-sales playbook while traveling frequently to London and Dublin.

Lead and build Disseqt's marketing function from scratch: create go-to-market strategy, positioning, demand generation, content, PR, partner co-marketing, and sales enablement to accelerate enterprise pipeline and establish thought leadership in AI governance.

Lead and operate cloud, ML, and data infrastructure: design/scale AWS/GCP environments, Kubernetes and CI/CD platforms, MLOps and model serving, streaming/data pipelines, SRE and DevSecOps practices, cost optimization, and enterprise-grade delivery pipelines while hands-on leading a lean team.

Advance detection and measurement in AI systems: expand jailbreak/adversarial libraries; build bias, fairness, and hallucination evaluation methodologies; develop interpretability techniques; translate research into engineering specs and methodology docs; publish work and represent the company with customers, regulators, and at conferences.

Own and design infrastructure architecture for cloud, hybrid, and on-prem AI deployments. Build scalable deployments, CI/CD/GitOps pipelines, observability stacks, and reusable IaC modules. Define SLOs, run incident response and postmortems, optimize performance and cost, ensure security and compliance, and collaborate with ML, backend, and product teams to deliver reliable enterprise AI platform services.

Own end-to-end frontend architecture for AI/DevOps products: build scalable design systems and component libraries, optimize rendering and performance, integrate real-time APIs, ensure security and accessibility, lead releases, mentor junior engineers, and drive frontend best practices across teams.

Design, train, and deploy NLP and ML models for classification, semantic scoring, and safety. Build containerized inference services, optimize CPU-only deployments, implement evaluation and observability pipelines, and integrate ML outputs with backend systems. Contribute to testing, red-teaming, and hybrid ML-rule systems to ensure reliable production AI.