<h3>The Team<\/h3>
\n<p>Forward Deployed Engineering owns how Tavily shows up technically in the field. The team sits at the intersection of customers, Product, Engineering, Sales, Partnerships, and Customer Success. <\/p>
\n<p>The Enterprise FDE motion focuses on Tavily\u2019s highest-value customers and strategic enterprise opportunities \u2014 from technical discovery and solution design through proof of concept, production rollout, adoption, and expansion. <\/p>
\n<h3><strong><span data-ccp-props="{}">The role<\/span><\/strong><\/h3>
\n<p>This is a full-time, on-site role based in our New York office. <\/p>
\n<p>As a Forward Deployed Engineer, Enterprise, you\u2019ll work directly with Tavily\u2019s largest and most strategic customers to design, prototype, and deploy production-grade AI systems powered by Tavily\u2019s API. You\u2019ll own the technical relationship across the customer lifecycle, helping enterprise teams move from early use case exploration to deployed, scalable agentic applications. <\/p>
\n<p>You\u2019ll be deeply hands-on: building RAG pipelines, agent workflows, evaluation loops, reference architectures, and custom integrations alongside customer teams. You\u2019ll also serve as a critical bridge between the field and our Product and Engineering teams, translating enterprise needs into roadmap signal. <\/p>
\n<p><strong><span data-contrast="auto"><span data-ccp-charstyle="Strong">Your responsibilities will include:<\/span><\/span><\/strong><span data-ccp-props="{"134233117":true,"134233118":true}"> <\/span><\/p>
\n<ul>
\n<li>Work directly with enterprise customers to understand their AI use cases, technical architecture, success criteria, and deployment requirements. <\/li>
\n<li>Lead technical discovery and solution design during pre-sales and expansion conversations. <\/li>
\n<li>Scope, build, and deliver proofs of concept that demonstrate clear business and technical value. <\/li>
\n<li>Design and implement production-ready integrations using Tavily\u2019s API, including RAG pipelines, agent workflows, internal tools, and industry-specific GenAI applications. <\/li>
\n<li>Partner with customer engineering, data, product, and AI teams to move use cases from prototype to production. <\/li>
\n<li>Monitor customer API usage patterns and recommend improvements to increase reliability, latency, coverage, and overall value. <\/li>
\n<li>Translate recurring customer needs, blockers, and technical patterns into clear product and roadmap input. <\/li>
\n<li>Create reusable enterprise assets, including reference architectures, integration templates, deployment guides, demo environments, and technical documentation. <\/li>
\n<li>Represent Tavily in customer architecture reviews, executive technical conversations, implementation check-ins, and post-deployment reviews. <\/li>
\n<li>Partner closely with Sales, Customer Success, Product, and Engineering to drive adoption, retention, and expansion across strategic accounts. <\/li>
\n<\/ul>
\n<p><strong><span data-contrast="auto"><span data-ccp-charstyle="Strong">We expect you to have:<\/span><\/span><\/strong><span data-ccp-props="{"134233117":true,"134233118":true}"> <\/span><\/p>
\n<ul>
\n<li>5+ years of software engineering experience, ideally in a customer-facing technical role such as Forward Deployed Engineer, Solutions Architect, Solutions Engineer, Sales Engineer, or Technical Consultant. <\/li>
\n<li>Strong hands-on engineering ability, especially with Python, APIs, backend systems, and production software development. <\/li>
\n<li>Experience building with LLMs, Retrieval-Augmented Generation, agent architectures, context engineering, and modern AI application stacks. <\/li>
\n<li>Experience working with enterprise customers, including technical discovery, POCs, solution design, stakeholder management, and production rollout. <\/li>
\n<li>Strong understanding of how enterprises evaluate, deploy, secure, and scale AI systems. <\/li>
\n<li>Ability to communicate clearly with both technical and executive stakeholders, including engineering leaders, product teams, AI teams, and technical decision-makers. <\/li>
\n<li>High autonomy, strong ownership, and comfort operating in a fast-moving startup environment. <\/li>
\n<li>Excellent written and verbal communication skills, with the ability to turn complex technical concepts into clear recommendations. <\/li>
\n<li>Based in New York City, or willing to relocate. <\/li>
\n<\/ul>
\n<p><strong><span data-contrast="auto"><span data-ccp-charstyle="Strong">It will be an added bonus if you have:<\/span><\/span><\/strong><span data-ccp-props="{"134233117":true,"134233118":true}"> <\/span><\/p>
\n<ul>
\n<li>Experience working with major agent or LLM orchestration frameworks such as LangChain, LlamaIndex, LangGraph, OpenAI Agents SDK, or CrewAI. <\/li>
\n<li>Experience with vector databases such as Pinecone, Weaviate, pgvector, Qdrant, or similar systems. <\/li>
\n<li>Experience with enterprise AI use cases in financial services, legal, consulting, enterprise SaaS, sales, marketing, or internal knowledge management. <\/li>
\n<li>Track record helping large customers move from POC to production. <\/li>
\n<li>Experience building internal tools, technical playbooks, demos, or reusable customer-facing assets. <\/li>
\n<li>Prior experience at a high-growth AI infrastructure, developer tools, or enterprise SaaS company. <\/li>
\n<\/ul><\/p>\n