Software Builder

Why this job is exciting

We're changing how we build. We're moving from teams where each developer owns a slice of an epic to builders who own the whole thing. A builder takes an idea and ships it: designed, implemented, evaluated, deployed. One person, full ownership, from first commit to production.

Agents made this possible. At Innovatrics, engineers develop with AI agents as the default way of working: you direct the work, the agents produce much of the code, and you own the result. Claude Code is our standard. The craft is judgment: knowing what to delegate, what to verify, what to build by hand, and how to prove the result is correct.

That last part is the heart of this job. We build biometric identity systems used by governments, banks, and security agencies: face recognition, fingerprint matching, identity verification at airports, at borders, in banking apps. This domain is regulated and adversarial. People probe our systems to defeat them. So we ship what we can stand behind, and proving correctness is part of the craft here, with the same weight as writing the code.

Where this sits

These roles map to the Software Engineer and Senior Software Engineer bands of our career framework. We'll calibrate level together during the process, based on the scope of ownership you've actually carried. The framework runs to Distinguished Principal, and the growth path is real.

What you'll be doing

• Owning features end to end: design, implementation, evaluation, deployment. Done means running in production.
• Directing AI agents through most of the build, then verifying the output as if you wrote every line yourself. You own agent output the same way you own your own code.
• Writing evals as part of delivery, so correctness is demonstrated rather than assumed.
• Improving the shared machinery: when an agent makes the same mistake twice, the context, prompt patterns, or harness gets fixed so it can't recur, for the whole team.
• Making deliberate calls on when AI is the wrong tool: security-sensitive code, novel biometric algorithms, deep-system work.
• Working across the stack your product needs, going wherever the problem is rather than waiting at a layer boundary.
• Collaborating with product and other engineers when you need input, without waiting for permission to move.

Requirements

We hire builders at 2 levels. The core is the same at both; the scope of ownership differs.

• Solid grounding in system design: you can reason about how a system behaves when things go wrong, including failures, retries, ordering, and scale, and you can defend the trade-offs you choose rather than just listing options.
• A developer who has shipped real things to real users, and can walk us through what broke and what they learned.
• Comfort across more than one language or stack, with genuine depth in at least one. Builders range wide; the best ones also go deep where their product demands it.
• Hands-on experience developing with AI agents (Claude Code or comparable), and a clear-eyed view of what they get wrong: plausible-but-broken logic, invented packages, missed edge cases.
• The habit of verification: you can say how you know a piece of work is correct, whether you wrote it or an agent did.
• A bias toward done over perfect, with correctness intact.
• Comfort with ambiguity: you can take a rough brief, scope it, and figure out the rest.

As a mid-level builder, on top of that:

• You own complex work autonomously: you take an Epic-sized requirement, structure it, and deliver it with light guidance.
• You write evals for your own work and invest in the team's shared agent setup beyond your own productivity.
• You can design a service end to end and stand behind its architecture under pushback, including how it handles failure and what you’d monitor to know it’s stuck.

As a senior-level builder, on top of that:

• You take a high-impact requirement and turn it into a shipped solution across team boundaries.
• You help define the team's agent strategy: which problems get agents, which get humans, which get pairs.
• You own the team's eval discipline and build the harnesses, context files, and agent skills the team depends on.
• You articulate taste: you can explain why one design beats another, spot hallucinated code in review, and say no with reasons.
• You develop the engineers around you, deliberately, so they form real skills while agents do the obvious work.
• You articulate taste: you can explain why one design or architecture beats another, including for distributed systems at scale, spot hallucinated code in review, and say no with reasons.

Good to have

• Experience with Java, Python, Go, C++, TypeScript, Kotlin, or Swift (different teams use different sets).
• Familiarity with biometrics, computer vision, or identity verification.
• Experience building evaluation pipelines, test harnesses, or CI quality gates.
• Cloud infrastructure (AWS, Azure, GCP) or container orchestration (Kubernetes, Docker).

Benefits

What we offer

• Direct impact: your work ships to global customers and gets used in the field.
• A culture that trusts you to own your work.
• Hybrid work from our Bratislava office, with flexibility on days and hours.
• Competitive salary benchmarked to market, reviewed annually.
• Hardware of your choice and a full AI tooling budget. We pay for the tokens; you bring the judgment.
• A team that takes its craft seriously and is honest about what isn't working.

Compensation

At Innovatrics, we offer highly competitive salaries because we value top talent who share our values and goals. Compensation is determined based on your level, skills, experience, qualifications, and location.

💶 Base Salary gross from 3,700 EUR - 5,000 EUR / Month. Compensation is tied to competency and technical evaluation, complemented by an attractive variable compensation scheme and a comprehensive benefits package supporting both your professional growth and well-being.

📈 Beyond base pay, we provide an attractive benefits package. You can learn more at: https://careers.innovatrics.com/benefits/

Interview Process

👋 Introduction Stage (~30 min.)

• Recruiter Screen

💻 Offline Assignment

• AI Assignment (3 hours) - A take-home exercise you'll complete independently, designed to assess your problem-solving approach and hands-on technical skills relevant to the role.

🧑‍💻 Onsite Interview (~2 hours)

• An in-person session with our technical team and Hiring Manager, focusing on your problem-solving approach, technical knowledge, and a walkthrough/discussion of your completed assignment.

🎯 Final Stage (~30 min.)

• CARES Interview: Final conversation with our CARES committee to ensure alignment with our core values—Collaboration, Accountability, Respect, Excellence, and Shared Mission.
• Reference checks and background verification

We encourage candidates to request additional conversations with anyone they would like to meet.