Member of Technical Staff

Flatfile; United States; On-site; USD 200,000 - 250,000; Full time

Job summary

Obvious is seeking a Full-Stack Product Engineer in the United States to bridge front-end and back-end work with AI-enabled features. You will own end-to-end product initiatives, ship multiple PRs quickly, and collaborate with designers, data scientists, and product managers.

You will build robust web apps using TypeScript/React, modern APIs, and AI integrations, focusing on agent-facing UX, memory management, and scalable architecture.

Qualifications

• Strong full-stack expertise with TypeScript/React and API/backend experience.
• Proven track record shipping end-to-end product features.
• Experience building agent-facing UX and AI integrations is a plus (eval harnesses/feedback loops).

Responsibilities

• Ship multiple PRs on first days and drive full-stack feature development from concept to deployment.
• Collaborate on the design and implementation of user-facing features that improve the experience.
• Build robust, performant web applications using modern frontend and backend technologies.
• Identify opportunities to optimize existing systems.
• Contribute to architectural decisions that shape the product.
• Set the UX of agent products as a standard in the product.
• Build AI/LLM integrations as core features, not bolt-ons.

Skills

TypeScript/React

Frontend development

API design

Backend development

AI/LLM integration

End-to-end ownership

Problem solving

Communication

Job description

Full-Stack Product Engineer

About Obvious

We’re building an AI‑native workspace—an operating system for work that puts co‑intelligence at the center. Start with data or an idea, describe your goal, and Obvious goes to work: running analysis, searching the web, writing documents, generating tables, designing presentations, visualizing data, building dashboards, and more.

As Steve Jobs imagined the personal computer as a bicycle for the mind, Obvious imagines AI as a garden for the mind. Less mechanical acceleration. More organic cultivation.

What if, instead of just vibe coding, you could vibe‑work? What if getting from idea to done wasn’t so opaque, stubborn, and high‑latency?

What if there was a way to consistently deliver work that feels like it came from the best version of you on your best day?

That’s Obvious.

Why we're hiring for this role

While we've made significant progress with our AI features like search, data enrichment, modes, artifact generation, coding, and more, we're just scratching the surface of what's possible.

We need engineers who can bridge the gap between powerful AI models and production-ready experiences that solve real user problems.

This isn't just about writing prompts – it's about building resilient systems that can handle the unique challenges of working with AI at scale and can solve some of the industry's most interesting problems like memory, agent-to-agent collaboration, non-deterministic repeatability, and more.

We are small and talent-dense. Among our founding team, we have world-class builders, former founders, and leaders from companies like Netflix, Google, Uber, Meta, Dropbox, Instacart, Shopify, Apple, Datadog and Twitter (X). If you're excited to solve some of the world's most challenging problems and build Al that can deliver on real‑world objectives, join us.

About Obvious

We're building an AI‑native workspace—an operating system for work that puts co‑intelligence at the center. Start with data or an idea, describe your goal, and Obvious goes to work: running analysis, searching the web, writing documents, generating tables, designing presentations, visualizing data, building dashboards, and more.

As Steve Jobs imagined the personal computer as a bicycle for the mind, Obvious imagines AI as a garden for the mind. Less mechanical acceleration. More organic cultivation.

What if, instead of just vibe coding, you could vibe‑work? What if getting from idea to done wasn't so opaque, stubborn, and high‑latency?

What if there was a way to consistently deliver work that feels like it came from the best version of you on your best day?

That's Obvious.

Why we're hiring for this role

We've made real progress on the AI features that make Obvious work—search, data enrichment, modes, artifact generation, coding—and we're still only scratching the surface of what's possible.

This is a generalist product engineering seat, firmly in the application space. We're looking for someone who translates customer problems into the most elegant, cost‑efficient solution—not someone chasing flashy tech for its own sake. That means bridging the gap between powerful AI models and production‑ready experiences that solve real user problems. This isn't about writing prompts. It's about building agent‑facing UX and the resilient systems behind it: memory, agent‑to‑agent collaboration, non‑deterministic repeatability.

We are small and talent-dense. Among our founding team, we have world‑class builders, former founders, and leaders from companies like Netflix, Google, Uber, Meta, Dropbox, Instacart, Shopify, Apple, Datadog, and Twitter (X). If you're excited to solve some of the industry's hardest problems and build AI that delivers on real‑world objectives, join us.

In this role you will:

• Ship at least 3 PRs on your first day


• Drive full-stack feature development from conception to deployment, owning key product initiatives end-to-end


• Collaborate on the design and implementation of user-facing features that improve the experience


• Build robust, performant web applications using modern frontend and backend technologies


• Identify opportunities for optimization and enhancement in existing systems


• Contribute to the architectural decisions that shape the product


• Set the industry standard for the UX of agent products


• Build AI/LLM integrations as a core part of the product, not a bolt-on—agent-facing UX, not just prompting

You will thrive in this role if you have:

• Genuine full-stack range, frontend-leaning: strong TypeScript/React paired with real API and backend chops—not a single narrow lane


• AI/LLM integration experience you can point to, not just talk about—production work building agent-facing features, ideally with the eval harnesses or quality feedback loops behind them


• An engineering bar we hold at staff level regardless of how you're titled—we'll ask about design-system fluency and client-server/UI performance judgment, not just ship velocity


• A track record of end-to-end ownership—driving ambiguous problems from first idea to shipped, not executing a spec handed down


• Strong problem-solving skills and attention to detail


• Excellent communication skills and the ability to work cross-functionally


• Willingness to work hard, move fast, and grow quickly in a rapidly changing environment


• A humble, team-first attitude and a desire to do whatever it takes to make the team succeed

Nice to have:

• Background in coding agents or multi-agent systems


• Informed opinions on agent orchestration


• Contributions to open-source projects or developer tools


• Previous experience at a high-growth startup

This role may not be a fit if:

• You need fully-specced requirements to operate—at our size, you'll define scope as often as you're handed it


• You see frontend and backend as separate lanes rather than one job


• You can't handle startup pace

Compensation Range: $200K - $250K