Enterprise AI Engineer – Onsite NYC

Tavily; Greater London; On-site; GBP 113,000 - 159,000; Full time

Job summary

Tavily is seeking a Forward Deployed Engineer, Enterprise, to work with our largest customers from our New York office. You will design, prototype, and deploy production-grade AI systems powered by Tavily's API, owning the technical relationship across the customer lifecycle.

You’ll build RAG pipelines and agent workflows, create reference architectures, and deliver integrated solutions while bridging field needs with Product and Engineering roadmaps.

Qualifications

• 5+ years of software engineering experience with customer-facing roles
• Strong hands-on engineering with Python, APIs, and backend systems
• Experience building with LLMs and Retrieval-Augmented Generation
• Experience working with enterprise customers through discovery, POCs, and rollout
• High autonomy and ability to communicate with technical and executive stakeholders
• Comfort in a fast-moving startup environment and ownership mentality

Responsibilities

• Work directly with enterprise customers to understand AI use cases and deployment requirements
• Lead technical discovery and solution design during pre-sales and expansion conversations
• Scope, build, and deliver proofs of concept demonstrating business and technical value
• Design and implement production-ready integrations using Tavily's API
• Collaborate with customer engineering, data, product, and AI teams to move use cases to production
• Monitor API usage and propose improvements for reliability and latency

Skills

Python

APIs

Backend systems

LLMs

RAG pipelines

Agent architectures

Context engineering

Production software development

Enterprise communication

Stakeholder management

Tools

Tavily API

LLM integrations

Job description

Tavily is seeking a Forward Deployed Engineer, Enterprise, to work with our largest customers from our New York office. You will design, prototype, and deploy production-grade AI systems powered by Tavily's API, owning the technical relationship across the customer lifecycle.

You’ll build RAG pipelines and agent workflows, create reference architectures, and deliver integrated solutions while bridging field needs with Product and Engineering roadmaps.