AI-powered talent acquisition and internal mobility platform
SeekOut builds AI-driven recruitment and talent redeployment software for mid-market enterprises. The tech stack—Azure, AWS, GCP, C#, Java, React, plus Greenhouse and Rippling integrations—reflects a multi-cloud, polyglot backend typical of platforms managing high-volume talent data. Active projects center on LLM-powered workflows and low-latency infrastructure, while pain points around scaling ingest and data fragmentation suggest the platform is handling recruitment volume at scale.
SeekOut operates a software platform designed to help organizations hire and redeploy talent using agentic AI. The product serves mid-market recruiting teams and HR departments, combining machine-learning-driven candidate sourcing with internal mobility features. The platform integrates with core HR systems (Greenhouse, Rippling, Okta) and analytics tools (Tableau, Power BI, Mixpanel), enabling data-driven talent decisions. The company is headquartered in Bellevue, Washington, and operates a distributed engineering organization across the United States and India.
SeekOut runs on Azure, AWS, and GCP across cloud providers, with C# and Java for backend services, React for frontend, and integrations with Greenhouse, Rippling, Okta, Salesforce, and Tableau for HR operations and analytics.
Yes. SeekOut has 2 active engineering roles open with accelerating hiring velocity, including senior-level positions. The company also has open product, HR, and support roles, hiring primarily in the United States and India.
Current project focus includes AI-powered recruiting features and LLM-powered workflows, core platform services with data pipelines, and scalable low-latency infrastructure to handle high-volume candidate and talent data.
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SeekOut's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.