Opportunities in United States

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America is strongest when ability can rise

The right person can change the trajectory of a team, a company, or an entire field.

But most hiring systems are built to avoid mistakes, not to discover extraordinary upside. They rely on the credentials that are easiest to read: the right degree, the right previous employer, or the right personal network. These filters, while convenient, are often very poor proxies for what someone can actually do.

When exceptional ability is missed, the loss is larger than one denied opportunity. A company loses performance. Coworkers lose a force multiplier. Ideas and businesses that could have existed never get built. A country that mistakes pedigree for ability does not merely distribute opportunity unfairly, it leaves growth on the table.

History suggests that better talent allocation has been a major source of American growth. When capable people reach the work where they can contribute most, workers rise, companies become more productive, and the benefits can spread through new ideas, stronger teams, families, and communities.

MeritFirst is building the infrastructure to make that the default. We create objective, efficient ways for people to demonstrate critical thinking, problem-solving, adaptability, and execution - and help companies hire based on demonstrated ability rather than pedigree alone.

For the worker, that means upward mobility. For the company, better performance. At scale, it can mean national growth.

The role

MeritFirst’s product has to do something much harder than move information around: it has to create a signal that deserves to influence consequential decisions about people.

Candidates must trust that they have a fair opportunity to demonstrate what they can do. Employers must trust that the resulting signal predicts performance better than the credentials they already use. Earning that trust requires exceptional product judgment, rigorous measurement, and software that is reliable, explainable, and built with care.

We’re looking for Software Engineers to help build that system from first principles. You will work directly with our founder, product team, candidates, and employers to shape and build the MeritFirst platform - from the candidate experience and assessment engine to employer workflows, evaluation systems, and the infrastructure beneath them.

This is not a role where a roadmap arrives fully specified. You will help determine what should exist, reduce ambiguous problems to their essential parts, ship the first version, observe how it behaves in the real world, and improve it quickly.

One day you may be designing a new assessment experience. The next, you may be debugging an edge case in production, working through an evaluation methodology with an assessment expert, simplifying an employer workflow, or deciding which manual process should become software.

AI gives engineers extraordinary new leverage, and we intend to use it. But our standard is not code that looks plausible or was produced quickly. It is a system we understand, can explain, can test, and can trust.

We expect our engineering team to have deep technical foundations while using modern tools to multiply judgment not replace it.

What you’ll build over time

The responsibilities below describe the full mandate of the engineering function over time, not a day-one checklist for one person.

You will begin by taking ownership of the highest-leverage product and technical problems, shipping directly to users, and developing a deep understanding of where software can most improve the candidate-to-hire loop. From there, you will help build the systems and engineering team that allow MeritFirst to scale.

• Build the core product. Create candidate and employer experiences that make it easy to demonstrate ability, understand the resulting signal, and act on it.

• Build a flexible assessment platform. Develop the primitives that allow us to create, deliver, evaluate, and continuously improve rigorous assessments and realistic work challenges across many kinds of roles.

• Own problems end to end. Move from understanding the user and shaping the product through system design, implementation, deployment, observation, and iteration. You will own outcomes, not tickets.

• Turn difficult human workflows into excellent software. Work closely with assessment experts, operators, and users to understand what should be automated, what should remain human, and how the two should fit together.

• Build evaluation systems worthy of trust. Make results consistent, interpretable, auditable, and resistant to gaming. Design appropriate human review, testing, and safeguards into systems that affect real careers.

• Close the learning loop. Connect assessment performance, employer decisions, and on-the-job outcomes so the product becomes more useful and predictive over time.

• Use AI where it earns its place. Apply models where they materially improve assessment creation, evaluation, or the candidate and employer experience - and build the evaluations and guardrails required to know whether they are actually working.

• Make trust a technical requirement. Treat reliability, security, privacy, accessibility, and candidate experience as foundational product properties rather than cleanup work.

• Strengthen the technical foundation. Improve architecture, testing, observability, performance, and developer velocity where the business requires it - without prematurely building infrastructure we do not yet need.

• Set the engineering standard. Establish the technical judgment, operating habits, and quality bar that future engineers will inherit. Help us identify and recruit the people who should join you.

Who will thrive here

You may have been an early engineer, technical founder, or senior individual contributor. You may have built an ambitious product at a startup, owned a critical system at scale, made meaningful open-source contributions, or developed exceptional ability outside a conventional path.

Your exact background matters less than evidence of unusual technical ability, product judgment, and ownership.

You will likely thrive here if:

• You have built and operated meaningful production software, not only prototypes or narrowly bounded features.

• You have exceptional technical foundations and can reason from first principles when existing abstractions stop helping.

• You can move fluidly between shaping the product, designing the system, writing the code, reading unfamiliar code, and understanding what happens in production.

• You have depth in at least one part of the stack and enough range to follow important problems wherever they lead.

• You are an excellent debugger. When something behaves unexpectedly, you form hypotheses, follow evidence, and keep going until you understand why.

• You combine speed with judgment. You know when to build the simplest thing that works, when to invest in a foundation, and how to avoid both perfectionism and careless debt.

• You have strong product instincts and care deeply about the person on the other side of the screen.

• You have built production software both with and without AI assistance. You understand where these tools create extraordinary leverage and where they can conceal shallow reasoning, brittle code, or false confidence.

• You treat AI-generated code like code written by someone you have never worked with: inspect it, test it, and take full responsibility for it.

• You communicate clearly, disagree directly, and make technical tradeoffs legible to non-engineers.

• You want your work to matter in the real world and care deeply about our mission.

This may not be the right role if

• You want requirements, architecture, and priorities to be fully specified before you begin.

• You prefer to remain within a narrow technical layer or consider product, user research, support, data work, or operations outside your job.

• You measure engineering quality primarily by code volume, feature count, or how quickly something can be generated.

• You rely on frameworks or AI tools without being able to explain, debug, and own the systems they help produce.

• You reach for elaborate architecture before understanding the problem or finding evidence that the scale requires it.

• You enjoy greenfield building but lose interest in operating, repairing, and improving what you ship.

• You want an established engineering organization, mature infrastructure, and settled operating playbook.

• You are looking for a predictable 9-to-5. We care about sustainable performance, but building an ambitious company from the ground up will sometimes require long days and exceptional intensity.

• You are more interested in the idea of meritocracy - or the current excitement around AI - than the difficult technical work required to build something people can trust.

Logistics

We practice what we preach: our hiring process is designed to surface demonstrated ability, not reward pedigree or interview polish. We care far more about what you can do rather than where you went to school or which logos appear on your resume.

You’ll move from a short initial screen to a conversation with a team member, a deeper role-relevant technical exercise, and final-round conversations focused on technical judgment, product sense, ownership, and mutual fit.

We may ask you to work both with and without AI assistance. We are not testing nostalgia or typing speed - we want to understand your technical foundations, how you reason, and how you use modern tools without surrendering judgment.

Along the way, you’ll experience the MeritFirst product firsthand, giving you a chance to evaluate what we’re building - and whether you’re excited to help shape it!

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