Quantum Software Engineer (US)

About Zapata Quantum

Zapata Quantum is shaping the future of quantum computing: setting the standards for what’s viable, valuable, and worth building. The Company powers quantum applications across cryptography, pharmaceuticals, finance, materials discovery, defense, and beyond, translating cutting-edge research into real-world impact.

Zapata is the only organization to have contributed across every technical area of DARPA’s Quantum Benchmarking program, giving it a uniquely comprehensive view of what it takes to make quantum computing work in practice. Now restructured and sharply focused, Zapata Quantum stands alone as the only publicly traded, pure-play quantum software company fully dedicated to unlocking quantum’s commercial potential.

We’re rebuilding at a pivotal moment for the industry—bringing together a team that will help define how quantum delivers value in the real world, with the opportunity for meaningful ownership as we shape the commercial path forward.

About the role

We are seeking a Quantum Software Engineer to build AI-powered tools that massively accelerate how quantum applications are designed and resource-estimated. You will fuse modern AI—LLMs, coding agents, and ML-based heuristics—with quantum circuit construction, compilation, and analysis, compressing workflows that currently take weeks of expert effort into hours. Your tooling will directly shape Zapata’s ability to evaluate and deliver quantum solutions across cryptography, pharmaceuticals, finance, materials discovery, and defense.

This position offers a high level of individual ownership and is well-suited to engineers who are excited to push the frontier of AI-assisted scientific software within a small, focused team. You will partner closely with algorithm scientists and customers to understand their design and resource-estimation workflows, then build tools that turn those workflows into automated, scalable pipelines. This position is classified as exempt under applicable wage and hour laws.

What you'll do

• Design and build AI-powered tools that accelerate quantum application design—from problem intake through algorithm selection, circuit construction, and validation
• Develop automated resource estimation pipelines that use LLMs and ML models to rapidly predict qubit counts, gate counts, and runtime for candidate quantum solutions
• Build agentic workflows that orchestrate quantum SDKs, compilation passes, simulators, and analysis tools
• Integrate state-of-the-art AI coding assistants and LLM APIs directly into internal scientific tooling to compress expert-led workflows into automated pipelines
• Benchmark and continuously improve the accuracy, speed, and reliability of AI-driven tooling against expert-curated baselines
• Collaborate closely with quantum algorithm scientists to capture their reasoning and encode it into reusable AI-driven tools
• Deliver high-quality software with minimal supervision, demonstrating autonomy in execution and technical decision-making

Qualifications

• Strong software engineering fundamentals, including testing, code review, and CI/CD practices
• BS or MS in Computer Science, Physics, Engineering, or a related field, or equivalent professional experience
• Demonstrated experience shipping software that leverages LLMs, AI agents, or other machine learning components
• Proficient programming skills in Python, with working knowledge of modern LLM APIs (Anthropic, OpenAI, or equivalent) and tool-use / function-calling patterns
• Deep familiarity with AI-assisted development workflows (Claude Code, Cursor, or similar) and a drive to use them to massively accelerate your own output and that of the team
• Familiarity with quantum computing concepts and a willingness to learn quantum algorithms and resource estimation in depth
• Ability to work independently and manage deliverables with minimal oversight
• Strong judgment about when to apply AI and when not to
• A commitment to measuring tool quality against expert baselines

Desired Programming Skills

• Python — for tooling, scientific code, and LLM-powered applications
• LLM APIs and tool-use / function-calling patterns (Anthropic, OpenAI, or similar)
• Agent frameworks and orchestration (LangGraph, pydantic-ai, or custom harnesses)
• Quantum SDKs (Qiskit, Cirq, PennyLane, or similar) for scripting design and estimation workflows
• AI-assisted development (e.g., Claude Code)
• Git and modern CI/CD tooling
• Evals and benchmark design for AI systems
• Software testing frameworks (pytest, hypothesis)
• NumPy, SciPy, and the scientific Python stack
• Retrieval-augmented generation and vector databases
• Containerization (Docker) and cloud infrastructure (AWS, Azure, or GCP)
• Prompt Engineering

Preferred Experience

• Demonstrated experience shipping software that leverages LLMs, AI agents, or other machine learning components
• Experience building developer tools, scientific workflows, or research automation that leverages AI to speed up expert work
• Strong communication skills and comfort collaborating across research and engineering teams

Originally posted on Himalayas