Forward Deployed Engineer, Enterprise - Tavily

Nebius•New York, NY

8d•$179,500 - $224,300•Onsite

About The Position

Nebius is building a full-stack AI cloud platform for the global AI economy, supporting developers and enterprises from data and model training through to production deployment. Tavily, a part of Nebius, is developing the search engine for AI agents, powering agentic applications and real-time reasoning by connecting LLMs to high-quality web content. The Forward Deployed Engineering team at Tavily focuses on the technical engagement with customers, sitting at the intersection of customers, Product, Engineering, Sales, Partnerships, and Customer Success. The Enterprise FDE role specifically targets Tavily’s highest-value customers and strategic enterprise opportunities, managing the technical relationship throughout the customer lifecycle, from discovery and solution design to proof of concept, production rollout, adoption, and expansion.

Requirements

3+ 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.
Strong hands-on engineering ability, especially with Python, APIs, backend systems, and production software development.
Experience building with LLMs, Retrieval-Augmented Generation, agent architectures, context engineering, and modern AI application stacks.
Experience working with enterprise customers, including technical discovery, POCs, solution design, stakeholder management, and production rollout.
Strong understanding of how enterprises evaluate, deploy, secure, and scale AI systems.
Ability to communicate clearly with both technical and executive stakeholders, including engineering leaders, product teams, AI teams, and technical decision-makers.
High autonomy, strong ownership, and comfort operating in a fast-moving startup environment.
Excellent written and verbal communication skills, with the ability to turn complex technical concepts into clear recommendations.
Based in New York City, or willing to relocate.
Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire.

Nice To Haves

Experience working with major agent or LLM orchestration frameworks such as LangChain, LlamaIndex, LangGraph, OpenAI Agents SDK, or CrewAI.
Experience with vector databases such as Pinecone, Weaviate, pgvector, Qdrant, or similar systems.
Experience with enterprise AI use cases in financial services, legal, consulting, enterprise SaaS, sales, marketing, or internal knowledge management.
Track record helping large customers move from POC to production.
Experience building internal tools, technical playbooks, demos, or reusable customer-facing assets.
Prior experience at a high-growth AI infrastructure, developer tools, or enterprise SaaS company.

Responsibilities

Work directly with enterprise customers to understand their AI use cases, technical architecture, success criteria, and deployment requirements.
Lead technical discovery and solution design during pre-sales and expansion conversations.
Scope, build, and deliver proofs of concept that demonstrate clear business and technical value.
Design and implement production-ready integrations using Tavily’s API, including RAG pipelines, agent workflows, internal tools, and industry-specific GenAI applications.
Partner with customer engineering, data, product, and AI teams to move use cases from prototype to production.
Monitor customer API usage patterns and recommend improvements to increase reliability, latency, coverage, and overall value.
Translate recurring customer needs, blockers, and technical patterns into clear product and roadmap input.
Create reusable enterprise assets, including reference architectures, integration templates, deployment guides, demo environments, and technical documentation.
Represent Tavily in customer architecture reviews, executive technical conversations, implementation check-ins, and post-deployment reviews.
Partner closely with Sales, Customer Success, Product, and Engineering to drive adoption, retention, and expansion across strategic accounts.