Senior Applied AI Engineer

About the RoleSenior Applied AI Engineer to build and ship AI-powered internal tools that dramatically speed up hiring, finance, and ops workflows.

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Lead end-to-end integration of LLMs, agent frameworks, embedding pipelines, and other AI tooling into production-ready internal solutions with strong ownership.Job DescriptionRoleAs a Senior Applied AI Engineer you will own the design, build, deployment, and maintenance of AI-powered internal tools that automate and accelerate company workflows.

You will work with LLMs, agent frameworks, embedding pipelines, and other emerging AI tooling to deliver production-ready solutions with end-to-end ownership.Key ResponsibilitiesRapidly prototype and ship AI-powered internal tools (days/weeks).Evaluate, integrate, and chain AI models, APIs, and frameworks (LLMs, agent frameworks, embedding pipelines, AI coding tools) into production-ready solutions.Integrate tools with existing systems (APIs, databases, third-party services) and ensure reliability at scale.Own deployments end-to-end: build, test, ship, monitor, and operate without constant supervision.Document and share tools so they provide compounding leverage across the company.Collaborate closely with non-technical teams to understand pain points and deliver automated solutions.RequirementsProven technical background with shipped projects (degree, bootcamp, or self-taught accepted).Experience building with modern AI tooling (LLMs, AI coding assistants, workflow automation).Strong ability to move fast, communicate clearly, and collaborate cross-functionally.Demonstrated ownership and startup/entrepreneurial mindset (built internal critical tools or founded/built impactful projects).Comfortable integrating with APIs, databases, and third-party services and operating production systems reliably.Fluency in English; German is a plus.Nice-to-have / BonusExperience with Make, n8n, Retool, Supabase or similar automation and internal tooling platforms. xcskxlj What you’ll getEnd-to-end ownership to build internal tooling from zero to one.A founder-level mandate to decide what gets built and how.Direct access to latest LLMs, agent frameworks, and AI coding tools and a culture that prioritizes speed and iteration.SkillsApplied AI AI systems integration Rapid prototyping End-to-end deployment API integration Database integration Monitoring and reliability Documentation Cross-functional communication Product ownership Entrepreneurial mindsetExperience LevelSeniorEmployment TypeFull TimeOwnership of internal tooling (zero-to-one)Fast iteration and ability to ship in days/weeksDirect access to latest LLMs, agent frameworks, and AI coding tools
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