Forward Deployed Engineer, Ecosystem
Tavily
| Company | Tavily |
| Category | Engineering |
| Location | New York |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 23 Jul 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (greenhouse) |
Description
About Tavily
We're building the search engine for AI agents. Our API powers agentic applications and real-time reasoning by connecting LLMs to high-quality, trustworthy web content. We work with some of the most innovative teams in AI — from startups shaping the ecosystem to enterprises deploying AI at scale.
The Team
Forward Deployed Engineering owns how Tavily shows up technically in the field. The team sits at the intersection of customers, Product, Engineering, Sales, Partnerships, Developer Relations, and Customer Success.
The Ecosystem FDE motion focuses on Tavily’s most important technical partners across the agentic AI stack — including model providers, agent frameworks, orchestration platforms, developer tools, ISVs, and emerging AI infrastructure companies.
The role
This is a full-time, on-site role based in our New York office.
As a Forward Deployed Engineer, Ecosystem, you’ll work directly with Tavily’s strategic partners to design, build, and launch solutions that make Tavily a core component of the modern agent stack. You’ll partner with external engineering and product teams to create high-quality integrations, reference implementations, demos, technical content, and joint solutions that help developers and companies build better AI agents.
You’ll be both a builder and a technical partner. You’ll ship code, shape integration strategy, influence product direction, and help Tavily become the default search and web access layer for agentic applications across the AI ecosystem.
Your responsibilities will include:
Work directly with ecosystem partners, including model providers, agent frameworks, orchestration platforms, AI developer tools, ISVs, 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, SDK 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, docs, 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, docs, tutorials, and reusable examples.
We expect you to have:
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 strong familiarity with the modern agent stack.
Experience building with LLMs, Retrieval-Augmented Generation, agent architectures, context engineering, and AI application frameworks.
Experience with at least one major agent or LLM 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 en
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