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Nebius

Runs GPU clouds for AI training and deployment

Forward Deployed Engineer - Ecosystem

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeNew York, NY, USA$112.7k - $183.9k

About the Job

Requirements

  • At least 3 years of software engineering experience, ideally in a partner-facing, developer-facing, or customer-facing technical role such as Forward Deployed Engineer, Solutions Architect, Developer Advocate, Solutions Engineer, Partner Engineer, or Sales Engineer.
  • Strong hands-on engineering ability, especially with Python, APIs, SDKs, backend systems, and developer-facing integrations.
  • Deep interest in the AI ecosystem and familiarity with the modern agent stack.
  • Experience building with large language models, Retrieval-Augmented Generation, agent architectures, context engineering, and AI application frameworks.
  • Experience with at least one major agent or large language model orchestration framework, such as LangChain, LlamaIndex, LangGraph, OpenAI Agents SDK, CrewAI, or similar tools.
  • Strong product intuition and ability to design integrations that are technically sound, easy to use, and valuable for developers.
  • Excellent written and verbal communication skills across engineering, product, partner, and developer audiences.
  • Ability to create clear technical content, including documentation, tutorials, example applications, demos, and reference architectures.
  • High autonomy, strong ownership, and comfort operating in a fast-moving startup environment.
  • Based in New York City or willing to relocate.

Responsibilities

  • Work directly with ecosystem partners, including model providers, agent frameworks, orchestration platforms, AI developer tools, independent software vendors, and infrastructure companies.
  • Design, build, and maintain high-quality integrations that make Tavily easy to adopt across the modern AI and agent stack.
  • Create reference implementations, example applications, software development kit examples, retrieval pipelines, agent workflows, demos, and technical templates.
  • Collaborate with partner engineering and product teams on integration design, technical tradeoffs, launch plans, and adoption goals.
  • Support technical partner conversations from early exploration through integration launch, developer adoption, and ongoing iteration.
  • Identify opportunities for Tavily to become embedded in partner products, frameworks, documentation, templates, and developer workflows.
  • Translate ecosystem patterns and partner feedback into product and roadmap input for Tavily’s Product and Engineering teams.
  • Partner with Sales, Partnerships, Developer Relations, Product, and Engineering to support strategic launches and joint technical initiatives.
  • Represent Tavily in partner reviews, technical workshops, developer communities, conferences, livestreams, and technical content.
  • Help build scalable ecosystem assets, including integration guides, demo environments, playbooks, documentation, tutorials, and reusable examples.

Desired Qualifications

  • Experience working with model providers, agent framework teams, developer platforms, AI infrastructure companies, or major technical partners.
  • Experience contributing to open-source projects, especially in the large language model, Retrieval-Augmented Generation, agent, or developer tools ecosystem.
  • Experience building or maintaining software development kits, integrations, plugins, templates, or framework adapters.
  • Experience speaking at developer conferences, hosting workshops, publishing technical content, or building developer communities.
  • Experience with vector databases such as Pinecone, Weaviate, pgvector, Qdrant, or similar systems.
  • Track record launching partner integrations or developer-facing technical initiatives that drove meaningful adoption.
  • Prior experience at a high-growth AI infrastructure, developer tools, or open-source company.

About the Company

Nebius

Runs GPU clouds for AI training and deployment

Nebius runs an AI cloud for developers, researchers, and enterprises that train models and put them into production. Its AI Cloud combines GPU computing, storage, networking, and managed services, while Token Factory runs models through an API so teams do not manage the underlying servers. Customers rent computing and storage at usage rates or reserve capacity, choosing resources that fit short experiments or sustained production workloads. Beyond the cloud, the group owns Avride, which develops autonomous vehicles and delivery robots, and TripleTen, which teaches technical skills for people changing careers. The publicly listed group is headquartered in Amsterdam, Netherlands.

Company size
1,001-5,000
Company stage
IPO
Headquarters
Amsterdam, Netherlands
Founded
1997

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