# Forward Deployed Engineer, Enterprise - Tavily

**Company**: Tavily
**Location**: New York
**Work arrangement**: onsite
**Experience**: senior
**Job type**: full-time
**Salary**: $179,500-$224,300 USD
**Category**: Engineering
**Industry**: Technology

**Apply**: https://job-boards.greenhouse.io/nebius/jobs/4880295101?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_e97fdad4-431

## Description

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.

Your responsibilities will include:

- Working directly with enterprise customers to understand their AI use cases, technical architecture, success criteria, and deployment requirements.

- Leading technical discovery and solution design during pre-sales and expansion conversations.

- Scoping, building, and delivering proofs of concept that demonstrate clear business and technical value.

- Designing and implementing production-ready integrations using Tavily's API, including RAG pipelines, agent workflows, internal tools, and industry-specific GenAI applications.

- Partnering with customer engineering, data, product, and AI teams to move use cases from prototype to production.

- Monitoring customer API usage patterns and recommending improvements to increase reliability, latency, coverage, and overall value.

- Translating recurring customer needs, blockers, and technical patterns into clear product and roadmap input.

- Creating reusable enterprise assets, including reference architectures, integration templates, deployment guides, demo environments, and technical documentation.

- Representing Tavily in customer architecture reviews, executive technical conversations, implementation check-ins, and post-deployment reviews.

- Partnering 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.

Compensation:

- Base Compensation Range: $179,500-$224,300 USD

Benefits & Perks:

- Competitive compensation

- Career growth and learning opportunities

- Flexibility and ownership

- Collaborative and innovative culture

- Opportunity to work on impactful AI projects

- International environment and talented teams

## Skills

### Required
- Python
- APIs
- backend systems
- production software development
- LLMs
- Retrieval-Augmented Generation
- agent architectures
- context engineering
- modern AI application stacks

### Nice to have
- LangChain
- LlamaIndex
- LangGraph
- OpenAI Agents SDK
- CrewAI
- Pinecone
- Weaviate
- pgvector
- Qdrant

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Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/nebius/jobs/4880295101?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)