Jobs at Scale AI

As an Applied AI Engineer, you will build AI applications for public sector clients, create and evaluate datasets, and collaborate with teams to address challenges using AI solutions.

As a Software Engineer, you will develop backend services for AI applications, optimize cloud infrastructure, and manage production-level deployments.

The Machine Learning Engineer will design, train, deploy, and evaluate AI models to address public sector challenges, ensuring high-quality data training and evaluating systems.

Lead strategic planning and execution for the Scale Generative AI Platform, owning technical scoping, architecture, and production launches. Coordinate cross-functional teams (platform engineering, Core ML, Research, Product), translate infrastructure metrics into roadmaps, mitigate deployment risks, define SLOs, drive developer velocity, and report adoption and reliability metrics to executive leadership to ensure scalable, secure, production-grade GenAI infrastructure.

Own end-to-end delivery of enterprise AI programs: manage timelines, risks, dependencies, and cross-functional integration. Translate technical complexity for engineering and executives, modernize agile workflows, and define program health metrics to drive adoption and scalable, reliable agentic solutions.

Lead development and scaling of an enterprise generative AI platform. Work across backend, frontend, and ML/LLM integrations, own major product areas, deliver high-velocity experiments, and ensure scalability and reliability from concept through production.

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.

Build and scale an enterprise Generative AI platform. Own large product areas across backend and frontend, develop reliable Python backend services, integrate LLMs, vector databases, and AI infrastructure, work with distributed systems and data pipelines, and ship features quickly while collaborating with product, ML, and infrastructure teams.

Build and operate core retrieval and knowledge representation systems for a generative AI platform: design RAG pipelines, embeddings, indexing, vector-store integrations, knowledge graphs/ontologies, evaluation frameworks, and production ML backend services while collaborating across product, ML, and infra teams and shipping enterprise-grade features.

The AI Applications Ops Lead will design and maintain production AI applications, ensuring their reliability and performance across international government agencies while bridging technical insights to officials.

The Lead Counsel will expand Scale's Global Public Sector business, negotiate commercial agreements, manage public tenders, ensure compliance, and partner with various teams in the organization.

Manage engineering teams to deliver AI-driven applications, oversee product lifecycle, mentor engineers, and collaborate cross-functionally.

Lead and own EMEA-specific assurance and certification programs (GCC, UK, EU), map controls, collect evidence, manage gaps and auditors, extend global certifications (SOC2, ISO), support customer assurance, legal and procurement compliance, and coordinate audits and regional regulatory engagement.

Lead the Forward Deployed Engineering team, overseeing AI deployment and production excellence for major enterprise accounts while enhancing team capabilities and organizational standards.

The Staff Technical Product Manager will own the product roadmap for Global Defense, design AI products, collaborate with engineers, and understand defense workflows to drive product outcomes.

As a Solutions Engineer, you'll engage with customers to design AI solutions, deliver demos, and collaborate with teams, ensuring technical needs are met.

As a Principal AI Ops Architect, you will lead full-stack AI application lifecycle management, ensuring reliability and compliance while developing impactful AI solutions for international government clients.

As a Machine Learning Engineer, you'll train and deploy ML models for enterprise clients, work on deep learning solutions, and interface with product teams to enhance AI applications.

The Product Manager will lead the development of AI solutions, manage cross-functional teams, and drive product strategy, focusing on customer needs and enterprise applications of ML-powered products.