Most engineering jobs start with a ticket. This one starts with a customer problem.
At Metaview, you will talk directly to the people using what you build. You will decide what should exist, build the consequential parts across the stack, put it in front of customers, and stay responsible for what happens next.
There is no chain of handoffs between product, design, engineering, support, and the customer. The person closest to the problem owns the result.
Coding was first. Recruiting is next. We are building it.Metaview is an applied AI lab building AI coworkers for some of the world’s most ambitious recruiting teams. Hear directly from our customers. The challenge is not another chatbot. It is software that can pursue a hiring objective, act across real workflows, ask for judgment at the right moment, and earn a customer’s trust.
Founded by Siadhal Magos and Shahriar Tajbakhsh, who scaled Uber and Palantir, we have raised more than $50M and are growing 5x year over year.
AI coding agents are part of the job, not a perk. Engineers routinely run several in parallel for exploration, implementation, and review. We assess both sides of the craft: how well you direct agents and how well you reason, code, and debug on your own. One interview exercise is completed without AI.
Our operating value is velocityVelocity means reducing the time from customer evidence to a reliable product change. It does not mean trading away quality. We ship small changes daily, including Fridays, because the engineer who ships owns production behavior, recovery, and the next revision. Process stays light because customer context and ownership are direct.
No one will hand you a polished specification. You will be expected to understand the customer, form an opinion, choose a path, and get working software into use. You will also own quality, production behavior, and the revision that follows the first release.
AI agents help our small team ship roughly 8x more product changes than a year ago. The engineer remains accountable for architecture, review, implementation quality, and production behavior.
What you will build and ownYou will work on problems such as:
building agents that can pursue recruiting objectives over days, know when to ask for judgment, and recover safely when a model or tool fails;
turning interview and hiring-team conversations into actions, with interfaces that let recruiters understand, correct, and trust the result;
designing permissions, controls, and recovery paths for agents acting in customer systems;
building the interface, APIs, data model, and production behavior of the same customer workflow; and
turning repeated product patterns into simple primitives that support many recruiting workflows.
In your first 3 to 6 months, you should independently own and ship a bounded customer outcome from problem definition through rollout and iteration. The size of that outcome will reflect your level, but the operating model is the same: make product and technical decisions, contribute the consequential code, and own the production result.
You will probably thrive here ifYou have personally shipped software for external users and owned a meaningful outcome from problem definition through production.
You have real depth in at least one technical area and can cross product, frontend, and backend boundaries when the outcome requires it.
You use AI coding agents heavily and can still design, implement, review, and debug independently.
You want direct customer contact, hands-on implementation, and responsibility after launch.
You naturally start with the customer problem rather than the requested feature.
You have strong product opinions and change them when evidence proves you wrong.
This opening spans mid-level and staff+ scope under the same hands-on operating model. At mid-level, you will independently own a bounded customer outcome across product and implementation. At staff+, you will still write code while setting direction for a broader area, making hard architectural tradeoffs, and raising the quality of decisions around you. We level on demonstrated scope, not years served.
This is a hands-on product IC role. It is not a people-management or model-research role.
Our stack includes React, TypeScript, Python, AWS, Postgres, and S3. Experience with these exact technologies is not required.
What you want to knowWe work together in person in San Francisco. This is not a remote role with occasional office attendance. Decisions are made by the people closest to the customer and the code. Read our unfiltered Slack to see how that works in practice.
We pay in the top 10% of the SF market through salary and meaningful equity. We re-benchmark against the market twice a year and adjust when compensation drifts.
Our process is fast and direct. It is not unusual to hear back the same day.
Metaview’s internal IC title is Member of Product Staff, Engineer. For this opening, level and compensation are set at mid-level or staff+ based on demonstrated scope. The work remains hands-on at every level.
We offer competitive option grants so we are all owners.
We sponsor work visas and support the immigration process from start to finish.
In the US, we cover 100% of medical, dental, and vision premiums for you and your dependents.
Time off is unlimited. Take the time you need.
Skills Required
- Experience shipping software for external users and owning meaningful outcomes from problem definition through production
- Depth in at least one technical area with ability to work across product, frontend, and backend boundaries
- Ability to use AI coding agents while independently designing, implementing, reviewing, and debugging software
- Willingness to work directly with customers and own production outcomes after launch
- Strong product judgment and customer-problem-oriented thinking
- Hands-on individual contributor orientation rather than people management or model research
- Experience with React, TypeScript, Python, AWS, PostgreSQL, or Amazon S3
- Ability to work in person in San Francisco
Metaview Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Metaview and has not been reviewed or approved by Metaview.
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Healthcare Strength — Private medical insurance via a named provider is highlighted for UK/EU hires, indicating robust health coverage in those markets. Feedback suggests this is a notable plus for a growth-stage startup.
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Leave & Time Off Breadth — A take-what-you-need PTO policy is promoted alongside EU-remote flexibility. Feedback suggests this provides generous latitude for time away.
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Equity Value & Accessibility — Equity grants are presented as a meaningful part of offers, making ownership a core component of rewards. Feedback suggests this aligns with packages typical of companies at this stage.
Metaview Insights
What We Do
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