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 engineering, product, partner, and developer audiences.
- Ability to create clear technical content, including documentation, tutorials, example apps, 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.
Bonus Points
- 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 LLM, RAG, agent, or developer tools ecosystem.
- Experience building or maintaining SDKs, 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.
Key employee benefits:
- Health insurance: 100% company-paid medical, dental and vision coverage for employees and families
- 401(k) plan: Up to 4% company match with immediate vesting
- Parental leave: 20 weeks paid for primary caregivers, 12 weeks for secondary caregivers
- Remote work reimbursement: Up to $85/month for mobile and internet
- Disability & life insurance: Company-paid short-term, long-term and life insurance coverage
Compensation
We offer competitive compensation packages. The actual compensation offered within the listed range will be determined based on job-related factors, including experience, skills, qualifications, and the level at which the candidate is hired, consistent with applicable law.
Pay Transparency
We offer competitive compensation and benefits packages. Actual compensation will be determined based on job-related factors, including experience, skills, qualifications, the level at which the candidate is hired, and geographic location, consistent with applicable law.
Pay Transparency
We offer competitive compensation and benefits packages. Actual compensation will be determined based on job-related factors, including experience, skills, qualifications, the level at which the candidate is hired, and geographic location, consistent with applicable law.
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