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# ZK Proof Engineer

Review the role, location requirements, compensation details, and application process before deciding whether this opportunity fits your next career move.

[Apply for this job](#job-application)[View company](https://jobicy.com/company/axiom.md)Share31 Aug 2026Published15Listing views1Application actions30 Sep 2026Apply before  Opportunity details

## About this role.

AI SummaryAxiom is seeking a ZK Proof Engineer to build and optimize cryptographic code for zero-knowledge proof generation using its OpenVM zkVM framework. The role spans low-level systems, RISC-V, compiler tooling, database backends, ZK circuits, and high-performance prover optimization. Candidates need strong systems engineering judgment, a security-focused mindset, and proficiency in Rust, C/C++, or a comparable performant backend language. This is an early-stage, high-impact position with substantial technical ownership and a strong preference for in-person work in New York, while remote candidates are also considered.

## Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

### Job Complexity

5/5EasyHard

### Pace & Pressure

5/5RelaxedFast-paced

### Autonomy Level

5/5GuidedFull ownership

### Communication Load

4/5IndependentCollaborative

AI insightThis is a highly specialized systems and cryptography role requiring comfort with zero-knowledge proofs, performance optimization, and interfaces across compiler, hardware, and database layers. The early-stage environment also demands independent technical decisions under a fast development pace.

## Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job medianMarket rate$187,500US market range$160k–$270k0$297k

AI insightThe disclosed yearly base salary range is USD 125,000 to USD 250,000, producing an offer midpoint of USD 187,500. For a specialized zero-knowledge proof and systems engineering role in the US, particularly one with New York alignment and early-stage technical ownership, an estimated market range is USD 160,000 to USD 270,000 yearly; equity may be additional.

## Core skills

Skills and capabilities most closely associated with this opportunity.

[Zero-Knowledge Proofs](https://jobicy.com/jobs?search_keywords=Zero-Knowledge%20Proofs.md)[Cryptography](https://jobicy.com/jobs?search_keywords=Cryptography.md)[Rust](https://jobicy.com/jobs?search_keywords=Rust.md)[C/C++](https://jobicy.com/jobs?search_keywords=CC%2B%2B.md)[Systems Programming](https://jobicy.com/jobs?search_keywords=Systems%20Programming.md)[Performance Optimization](https://jobicy.com/jobs?search_keywords=Performance%20Optimization.md)[RISC-V](https://jobicy.com/jobs?search_keywords=RISC-V.md)[LLVM](https://jobicy.com/jobs?search_keywords=LLVM.md)[ZK Circuits](https://jobicy.com/jobs?search_keywords=ZK%20Circuits.md)[Security Engineering](https://jobicy.com/jobs?search_keywords=Security%20Engineering.md)

Sample interview questionsHow would you approach optimizing a bottleneck in a zero-knowledge prover?I would first establish a reproducible benchmark and profile the prover to identify whether the constraint is arithmetic operations, memory access, serialization, parallelism, or field arithmetic. I would make one measurable change at a time, validate proof correctness with regression tests, and compare throughput, latency, and resource usage against the baseline. Any optimization would be reviewed for security implications and maintainability.

Describe how you would connect a RISC-V execution environment to a ZK proving system.

I would define a precise execution trace and constraints that prove correct instruction semantics, register and memory transitions, and control flow. The design would prioritize soundness and modularity, with clear interfaces between the VM, trace-generation layer, and proof backend. I would also profile trace size and constraint costs early, since these typically drive prover performance.

What makes Rust a suitable language for security-sensitive cryptographic systems?

Rust provides memory-safety guarantees without garbage collection, which helps prevent classes of vulnerabilities common in low-level code. Its type system, ownership model, and ecosystem support reliable concurrent and performance-sensitive implementations. I would still apply cryptographic engineering practices such as constant-time review where applicable, careful dependency auditing, and extensive property and adversarial testing.

How would you evaluate whether to adopt an LLVM or MLIR-based component in a small engineering team?

I would assess the concrete capability gained, integration cost, long-term maintenance burden, maturity of the ecosystem, and impact on performance and developer velocity. I would prototype against representative workloads and define success criteria before committing. The decision should favor the simplest architecture that meets correctness, extensibility, and performance requirements.

Tell us about a time you had to make a technical trade-off with incomplete information.

I would explain the decision context, identify the highest-risk assumptions, and gather enough data through targeted experiments or design reviews to compare alternatives. I would document the chosen trade-off, define rollback criteria, and communicate the rationale clearly to stakeholders. This approach maintains momentum while preserving the ability to revise the design as new evidence emerges.

About Us

Axiom is using zero-knowledge proofs to enable new types of verifiable and private software applications, starting with crypto and fintech. We are a small but incredibly strong team backed by the [best investors in crypto](https://blog.axiom.xyz/funding/). We’re looking for exceptional people who are excited to work on challenging and impactful problems in a fast-paced environment. Our office is in NYC and working in person in NY is our strong preference, but we’re open to remote candidates as well.

We recently released [OpenVM](https://blog.axiom.xyz/openvm), a performant and modular zkVM framework built for customization and extensibility. OpenVM allows developers to verify the correct execution of arbitrary computer programs in a flexible and performant way. We are building ZK-enabled products using OpenVM and supporting teams building on OpenVM.

The Role

We are looking for a ZK Proof Engineer who will implement and optimize cutting-edge cryptographic code for zero-knowledge proof generation. You will be responsible for building systems to interface between low-level computer systems like the RISC-V ISA, compiler frameworks like LLVM, and database backends and connecting them with cutting-edge zero-knowledge proof systems. The role will involve both optimizing ZK provers and implementing novel ZK circuits. Your work will require making design choices to enable rapid development of secure and efficient systems.

We are looking for someone with strong engineering design skills, the ability to work across the stack, and a security mindset. We also value the ability to make pragmatic technology choices which empower our small team without adding too much overhead.

Who you are

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You have a strong background in math/cryptography, or strong problem-solving skills and interest in zero-knowledge proofs.

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You have proficiency in Rust, C/C++, or a similarly performant backend language. We work primarily in Rust.

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You are extremely detail oriented and have a security mindset.

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You’ve worked on challenging software projects and have an eye for performance.

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You’re a clear communicator and value collaboration.

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You have a strong bias towards action.

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You have an extremely strong work ethic.

Bonuses

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You have experience with compiler frameworks like LLVM or MLIR.

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You’ve worked with aspects of low level computer architecture like RISC-V or programmed FGPAs or other custom hardware.

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You have experience with database backends, including experience with query planning or low level query engines.

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You’ve done research in mathematics, theoretical computer science, or theoretical physics.

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You have experience with low-level details of Ethereum

We welcome diverse backgrounds. Some non-traditional profiles that may be a good fit include high-frequency trading, math/physics/CS academia, and hardware engineering.

Why join us

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You’ll be one of the earliest employees with ownership to make key technical/product decisions.

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You’ll be working on groundbreaking tech that has the potential to be a key piece of infrastructure for the crypto industry.

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You’ll receive a competitive salary with equity.

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You will work with and receive mentorship from an exceptional team.

Our Team

Our founders Yi Sun and Jonathan Wang met while studying math at Harvard and have been working on ZK since 2021. Together, they wrote some of the most performant ZK circuits for elliptic curve cryptography and Ethereum data reads before starting Axiom.

Before Axiom, Yi was a professor at UChicago Statistics and did a math PhD at MIT. He was previously an advisor for Gauntlet and worked at an HFT startup from inception to profitable trading. Jonathan published number theory research in top math journals and did a math PhD at UChicago.

The rest of our small but incredibly strong team includes alums of Applied Intuition, Coinbase, Color, Neon, Google, and Perplexity as well as math / CS PhDs and IMO / IPhO / Codeforces winners. We look forward to working with you!

Show more

[Apply now >](https://jobicy.com/jobs/152237-zk-proof-engineer.md)

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