Jobs at Scale AI

Lead complex AI engineering engagements from client discovery through production. Build prototypes involving AI agents, RAG systems, evaluation pipelines, and data and knowledge platforms; define secure, reusable architectures; resolve difficult technical problems; mentor engineers; and advise senior clients on technical and business trade-offs. The role also contributes reusable capabilities to the core platform and requires travel to client sites as engagements require.

Own the AI behavior of production systems for public-sector clients, including agents, model integration, backend services, evaluations, guardrails, and observability. Lead root-cause analysis, optimize and adapt models, manage workstream delivery and client expectations, create reusable tooling, and mentor engineers. The role requires production AI/ML experience, evaluation design, client communication, regulated-data awareness, auditability, and reliable end-to-end ownership of AI systems.

Grow Scale’s UK AI business across public sector and enterprise markets. Responsibilities include researching accounts, building pipelines, developing partnerships, shaping AI opportunities, managing framework applications and public-sector tenders, and creating proposals and executive materials. The role combines business development, commercial strategy, customer engagement, and bid management in a fast-paced market-entry environment.

Build and evolve cloud-agnostic deployment and observability infrastructure across AWS, Azure, GCP, OCI, and on-premises environments. The role involves developing secure, reproducible deployment pipelines, expanding platform observability, debugging customer and internal deployment issues, responding to incidents, conducting root cause analysis, shaping product roadmaps, and leading architecture reviews and end-to-end infrastructure projects.

Build and evolve cloud-agnostic deployment and observability infrastructure across AWS, Azure, GCP, OCI, and on-premises environments. The role involves developing secure, reproducible deployment pipelines, improving platform observability, debugging production issues, responding to incidents, conducting root cause analysis, shaping the roadmap, leading architecture reviews, and owning infrastructure projects end to end.

Lead Scale’s commercial growth across UK civilian central government, owning pipeline, complex pursuits, framework and tender strategy, deal closure, and delivery alignment. Build relationships with senior stakeholders at departments such as HMRC, DWP, and NHS, while hiring and developing a small public-sector go-to-market team. The role requires experience selling technology or transformation services into UK government and navigating complex procurement environments.

Build and run EMEA GTM onboarding, centralize and maintain a sales knowledge base, deliver recurring enablement programs, and support priority deals by creating reusable playbooks and field-ready materials to help sellers communicate Scale's AI capabilities.

Lead end-to-end product design for Scale’s enterprise AI data products, including insurance AI, document processing, dashboards, data visualizations, editors, and forms. Create user flows, wireframes, mockups, and prototypes; collaborate with product, engineering, data science, and operations teams; advocate for users; identify product gaps; and contribute to the company design system.

Lead and grow Scale AI’s enterprise product design team, set design direction, hire and develop designers, and drive execution with Product and Engineering. Establish research practices, maintain high craft standards, contribute to the shared design system, and define interaction patterns for enterprise users working with AI agents and human-in-the-loop systems.

Lead end-to-end 0-to-1 product design for AI-driven B2B experiences serving government and enterprise clients across the Middle East. Translate stakeholder and client insights into concepts, prototypes, and polished visual designs while collaborating with product managers and engineers. Use research, data, and user insights to guide decisions, manage expectations, and ship impactful products. The role requires Arabic and English fluency, GCC experience, and familiarity with AI-powered design tools.

Build and ship production software for AI systems, including data pipelines, evaluation infrastructure, agentic applications, fraud detection, matching algorithms, and AI tooling. Interns work on full-stack product engineering, large-scale data systems, and customer-focused iteration while receiving mentorship. The role requires prior software engineering internship experience, shipped products, and familiarity with Python, TypeScript, React, and/or MongoDB.

Build and ship customer-facing AI products and software systems from day one. Responsibilities include developing full-stack applications, data pipelines, evaluation infrastructure, agentic AI tooling, fraud detection, matching algorithms, contributor tools, AI infrastructure, and customer service applications. Engineers work directly with customers, iterate quickly, and deliver reliable products capable of operating at large scale.

Lead development of production AI behavior, governance, and MLOps standards for high-risk public-sector systems. Architect and validate safety-focused AI components, build reusable agent and evaluation capabilities, advise executive clients on AI strategy, resolve severe model-safety incidents, and coach senior engineers while shaping the technical roadmap and recruitment.

Lead a team of Product Managers to integrate Scale products into complex enterprise and government environments. Hire and mentor PMs, translate bespoke field deployments into scalable product strategy, partner with Sales/GTM and EPD, unblock high-priority deployments, and ensure the voice of the field informs roadmap decisions.

As a Full-Stack Software Engineer, you'll lead the technical strategy for AI applications in the public sector, architecting frameworks, guiding development, and mentoring staff.

As a Senior Full-Stack Software Engineer, you will develop AI applications for public sector clients, design full-stack solutions, and manage cloud infrastructure while collaborating with cross-functional teams to address complex challenges.

Conduct empirical AI safety research with mentor guidance, owning projects from hypotheses and controlled experiments through analysis and technical writing. Build and debug evaluation harnesses, agent environments, datasets, monitoring methods, and post-training experiments. Investigate model failures, alignment, deception, misuse, multi-agent risks, and evaluation reliability. Produce reproducible code, experiment logs, research analyses, and papers for potential submission to leading machine learning conferences.