Senior Full Stack Engineer (Agentic Search) - Platform
Tavily is hiring a Senior Full Stack Engineer (Agentic Search) - Platform in New York, United States. It pays $147k-$224k a year and Level rates it ; you can apply on Tavily.
Level's read on this job
- Works on AI ●●●○ is how Level rates this software engineer role: the daily work is on AI products, without building the model.
- The posting mentions RAG and AI agents among its tools and skills.
- Level classes it as a senior role.
- Tavily has 12 other open roles on Level.
- Posted in the last few days.
AI in this role
About Tavily
We're building the infrastructure layer for agentic web interaction at scale. Our API is designed from the ground up to power Retrieval-Augmented Generation (RAG) and real-time reasoning in AI systems. By connecting LLMs to high-quality, trustworthy web content, we help developers build agents that are not only intelligent — but also informed.
We work with some of the most innovative teams in AI — from small startups shaping the ecosystem to the largest enterprises deploying AI at scale. Whether it's powering sales assistants, research copilots, or internal knowledge tools, we're the missing link between LLMs and the real world.
The Role
We are looking for a Senior Full Stack Engineer to build how developers and AI agents access our agentic web infrastructure. This role is based in our New York office, hybrid with the NYC team.
Our APIs are used by millions of developers and the AI agents acting on their behalf. The team owns the main API gateway, the customer platform (keys, usage, teams), identity and enterprise SSO, and the public interfaces to our product: the SDKs, CLI, MCP servers and other tools developers and agents use. You'll work closely with product, design and engineers across our R&D.
In this position, your responsibility will be to:
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Design and ship features end to end, from the interface to the services and data behind it
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Build and improve the API gateway: high traffic, low latency, reliable
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Turn usage, billing and team data into fast, usable interfaces: tables, charts, filters and forms
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Shape the self-serve journey from signup through activation
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Build and operate identity and team access in production: OAuth and OIDC, role-based access, SAML SSO and SCIM, on providers such as Auth0, Okta, WorkOS or Clerk
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Control who gets which features, with feature flags for staged rollouts and entitlements after rollout
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Improve the public interfaces developers and agents use: the SDKs, CLI, MCP servers and docs
You may be a good fit if you:
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Have 5+ years of full-stack engineering on customer-facing products or high-throughput APIs, in any mix of frontend and backend
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Are strong in backend engineering, ideally in Python. Go, C++ or C with some Python experience also fits
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Have built and operated latency-sensitive, high-QPS APIs: caching, async work, queues, retries and rate limiting, including long-running jobs and webhooks
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Have shipped production UI with a modern frontend framework such as React, Next.js or TanStack, ideally in TypeScript
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Have built data-heavy interfaces such as tables, charts and filters that stay fast
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Are effective in a mature, user-facing system: you have joined a complex codebase, ramped up fast, shipped safely under real traffic, and been on-call for it
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Have strong product and design sense, for interfaces and for APIs
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See your work through from design to production, explain trade-offs clearly to partners, navigate ambiguity, and use AI tools in how you build
Strong candidates may also:
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Have led a project or mentored others
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Have taken a product from 0 to launch
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Have built API-key issuance and lifecycle
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Have built MCP servers or tools for AI agents
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Have worked on billing or usage metering with Stripe, Metronome, Orb or similar
Why Tavily?
- Full ownership — small team, you own the entire infrastructure, not a slice of it
- Real scaling challenges — bursty scraping workloads, cache invalidation, multi-region, millions of daily requests
- AI-native company — your infra directly powers AI agents used by leading companies in the space.
Key employee benefits in the US:
- Health insurance: 100% company-paid medical, dental, and vision coverage for employees and families.
- 401(k) plan: Up to 4% company match with immediate vesting.
- Parental leave: 20 weeks paid for primary caregivers, 12 weeks for secondary caregivers.
- Remote work reimbursement: Up to $85/month for mobile and internet.
- Disability & life insurance: Company-paid short-term, long-term and life insurance coverage.
Pay Transparency
We offer competitive compensation and benefits packages. Actual compensation will be determined based on job-related factors, including experience, skills, qualifications, the level at which the candidate is hired, and geographic location, consistent with applicable law.
Base Compensation Range$147,200—$224,300 USDHow we rate this
Senior Full Stack Engineer (Agentic Search) - Platform at Tavily rates 64 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in software engineer jobs at this level
Pay
- This job starts at
- $147k
- Typical software engineer job
- $167k
This posting starts 12% below the typical software engineer job. See software engineer jobs
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- Describe a typical day in a role like this one: which parts run through AI directly?
- If you removed AI from this role, what would be left, and how do you decide what still needs a human?
Adapt your resume
- List these exact terms on your resume: RAG and AI agents. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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