Forward Deployed Engineer, Enterprise

Remote Worker LTD.; United States; On-site; USD 140,000 - 190,000; Full time

Job summary

Tavily is seeking a Forward Deployed Engineer, Enterprise, to work directly with our largest customers in New York City. You will design, prototype, and deploy production-grade AI systems via Tavily’s API, owning the technical relationship across the customer lifecycle.

Expect hands-on development of RAG pipelines, agent workflows, and custom integrations. You will bridge customer needs with Product and Engineering, guiding proofs of concept to production, and collaborating with cross-functional

Qualifications

• 5+ years of software engineering in a customer-facing technical role.
• Strong hands-on engineering with Python, APIs, backend systems.
• Experience building with LLMs, Retrieval-Augmented Generation, agent architectures.
• Experience working with enterprise customers across discovery, POCs, solution design, deployment.
• Ability to communicate clearly with technical and executive stakeholders.
• Based in New York City or willing to relocate.

Responsibilities

• Understand enterprise AI use cases, architecture, success criteria, and deployment requirements.
• Lead technical discovery and solution design in pre-sales and expansion conversations.
• Scope, build, and deliver proofs of concept with measurable value.
• Design and implement production-ready integrations using Tavily’s API (RAG pipelines, agent workflows).
• Collaborate with customer engineering, data, product, and AI teams to move use cases to production.
• Monitor API usage patterns and recommend reliability and latency improvements.
• Translate customer needs into roadmap input; create reusable assets and references.
• Represent Tavily in architecture reviews and executive technical conversations.
• Partner with Sales, CS, Product, and Engineering to drive adoption and expansion.

Skills

Python

APIs

LLMs

Agent architectures

Communication

Stakeholder management

Enterprise engagement

Tools

LangChain

LlamaIndex

Pinecone

Weaviate

Qdrant

OpenAI API

Weaviate

Qdrant

Job description

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, and Customer Success.

The Enterprise FDE motion focuses on Tavily’s highest-value customers and strategic enterprise opportunities — from technical discovery and solution design through proof of concept, production rollout, adoption, and expansion.

The role

This is a full-time, on-site role based in our New York office.

As a Forward Deployed Engineer, Enterprise, you’ll work directly with Tavily’s largest and most strategic customers to design, prototype, and deploy production-grade AI systems powered by Tavily’s API. You’ll own the technical relationship across the customer lifecycle, helping enterprise teams move from early use case exploration to deployed, scalable agentic applications.

You’ll be deeply hands-on: building RAG pipelines, agent workflows, evaluation loops, reference architectures, and custom integrations alongside customer teams. You’ll also serve as a critical bridge between the field and our Product and Engineering teams, translating enterprise needs into roadmap signal.

Your responsibilities will include:

• 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.

We expect you to have:

• 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.
• 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.

It will be an added bonus if you have:

• 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.