AI Jobs

This role works on AI-native vertical SaaS for construction logistics. It is relevant for builders who can deploy practical AI systems into customer operations and translate workflow needs into productized solutions.

This role implements, customizes, and optimizes AI phone-agent solutions for enterprise customers. It combines technical implementation, customer requirements translation, deployment, adoption, and measurable impact delivery.

This role designs tailored solutions for strategic customers using ElevenLabs voice and agent technology. It involves technical architecture, integrations, product features, and end-to-end ownership of high-impact customer challenges.

This role owns deployment, configuration, and ongoing management of AI data agents for enterprise customers. The work includes context ingestion, data pipeline integration, operational workflows, and agent orchestration tuning.

This role owns the lifecycle of AI products with banking clients, from deployment through production optimization and expansion. It translates regulated customer requirements into integrations between Titan's AI platform and bank systems.

This role builds AI growth workflows for internal use and customer-facing productization. It sits between product, growth, and customer success, turning live customer learnings into scalable AI workflow templates and product improvements.

This role leads customer deployments for Archie, an AI engineer for physical product domains. It connects AI reasoning capabilities with customer data, tools, design processes, and production implementation needs.

This role builds full-stack features across frontend, backend, and AI layers for an AI agent that runs and grows businesses. The work emphasizes shipping quickly with Next.js, TypeScript, LLMs, multi-agent systems, and AI-native UX.

This role builds the agentic layer of Raspberry's design platform. It includes agent architectures, orchestration, tool abstractions, multi-step creative workflows, and product interfaces that keep designers in control.

This role builds core systems that make AI agents usable in production, including runtimes, orchestration, reliability, tracing, debugging, evaluation, and coherent integrations with APIs and external data.