Forward Deployed Engineer, Partnerships
Role Overview
This mid-to-senior role involves embedding with partner technical teams to build and scale integrations, leading API troubleshooting, and developing joint solutions. As a Strategic Forward Deployed Engineer, you will represent Tavily at partner events, collaborate cross-functionally with Product and Engineering, and drive strategic programs to deepen partner technical capabilities. The hire will accelerate indirect revenue and execute on long-term go-to-market strategy through ecosystem expertise.
Perks & Benefits
This is a remote role, though the company prefers candidates based in or willing to relocate to New York City or San Francisco, implying some time zone alignment. You'll work in a fast-paced startup environment with opportunities for autonomy, external visibility through events and conferences, and cross-functional collaboration. Career growth is supported through enablement sessions and high-trust stakeholder relationships, typical of tech partnerships roles.
Full Job Description
About Tavily
Tavily is the external intelligence layer for AI agents and LLM-powered applications — connecting them to real-time, high-quality information.
We power the research and retrieval infrastructure behind leading AI products and platforms, working with partners like AWS, IBM, Snowflake, Databricks, and MongoDB.
Our mission is to make external knowledge instantly accessible to every AI system — and partnerships are how we scale that mission.
Role Overview
We’re looking for a Strategic Forward Deployed Engineer to build, operationalize, and scale Tavily’s enterprise and platform partnerships. This is a highly strategic role that blends technical excellence, ecosystem obsession, and business acumen. You will be the technical focal point for these partnerships - leading development, turning ideas into integrations, and communicating the better together story to different stakeholders. You will strengthen our relationships with key partners to accelerate indirect revenue, enable their AI practices, and execute on long-term GTM strategy.
Responsibilities
Strategic Technical Partner: Be a technical thought partner to the Tavily GTM team, providing technical expertise to better understand the partner landscape, driving key strategic programs, and identifying opportunities to deepen partner technical capabilities.
Embed with partner technical teams — support API troubleshooting and evangelize Tavily in our partner’s developer communities, develop joint solutions, codify reference architectures & best practices, publish blogposts, and accelerate time to deployment.
Represent Tavily externally — lead at partner events, workshops, and conferences; maintain high trust and visibility with alliance stakeholders and run enablement sessions for external GTM teams.
Collaborate cross-functionally — work closely with Product, Engineering, Marketing, and Sales to ensure alignment between partner strategy, GTM positioning, and integration roadmap.
Be the ecosystem expert — deeply understand each partner’s product strategy — and identify where Tavily fits best within it.
Ideal Profile
3+ years of software engineering experience, ideally in a customer-facing, consulting, or partner-focused role at a large company (e.g., Forward Deployed Engineer, Solutions Architect, Sales Engineer).
Obsession with AI ecosystem - strong engineering skills and experience working with the modern agent stack.
Deep understanding of Retrieval-Augmented Generation (RAG), LLMs, context engineering, and agent architectures.
Strong interpersonal skills and comfort working directly with technical stakeholders at enterprises and partners.
Fast learner, highly autonomous, and excited to work in a fast-paced startup environment.
Demonstrated success working with major cloud or enterprise ecosystems (AWS, Azure, GCP, IBM, MongoDB, Snowflake, Databricks).
Understanding of commercial and technical partnership structures (marketplace, rev-share, OEM).
Based in New York City, SF, or willing to relocate.
Interview Process
Intro Call – An informal chat to get to know you, your background, and your interest in AI.
Take-Home Exercise – A short assignment similar to the work you’d do on the job.
System Design Interview – A live problem-solving session to understand how you problem solve (we’ll share a study guide beforehand).
Final Meeting – A conversation with our leadership team.
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