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Zapata Quantum

Senior AI Software Engineer (US)

Posted 10 Days Ago
Remote
Hiring Remotely in United States
Senior level
Remote
Hiring Remotely in United States
Senior level
Design and build AI-enabled applications centered on knowledge graphs, ontologies, graph and vector databases, RAG, and agentic pipelines. Develop scalable backend systems, APIs, data pipelines, integrations, and interactive full-stack web applications. Make architectural decisions, integrate intelligent search and retrieval features, evaluate emerging technologies, and ship production code. Collaborate with product, design, domain experts, and leadership while contributing to engineering standards, quality, security, testing, and maintainability.
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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 hands-on Senior Software Engineer to design and build a knowledge graph, ontology, and AI-enabled application related to quantum computing and design. You will work across the stack, with particular focus on the architecture and implementation of knowledge graphs, ontologies, graph and vector databases, RAG, on a small but mighty engineering team. Building, maintaining, and designing scalable graph retrieval based AI applications.

This position offers a high level of ownership and is well suited to an engineer who is comfortable working across the stack, solving ambiguous technical problems, and remaining deeply involved in product development. You will be encouraged to experiment boldly with emerging technologies, evaluate new approaches, and apply them thoughtfully to unlock breakthrough performance and deliver outsized impact. 

This position is classified as exempt under applicable wage and hour laws and requires the regular exercise of independent judgment and discretion in leading the design, architecture, and development of software systems.


What you'll do

  • Design and build systems involving knowledge graphs, ontologies, graph and vector databases, RAG, and related AI-enabled application functionality.
  • Design and implement scalable agentic pipelines, involving custom agent tools, loops, and evaluation techniques for agentic systems
  • Design, architect, build, and continuously improve a modern, interactive web application, including selecting appropriate frameworks, and designing intuitive user interfaces..
  • Familiarity with cloud platforms and system design 
  • Make architectural and product-related technical decisions, exercising independent judgment when evaluating tools, technologies, tradeoffs, and design patterns.
  • Design and implement backend systems, data models, APIs, data pipelines, and integrations that support complex application functionality.
  • Integrate AI-enabled features such as intelligent search, retrieval, recommendations, contextual assistance, and other emerging application capabilities.
  • Collaborate with product, design, domain experts, and company leadership to translate business and user needs into practical technical solutions.
  • Remain deeply involved in software development, personally writing, testing, debugging, and shipping production code.
  • Contribute to engineering standards and best practices for software design, code quality, testing, documentation, security, and maintainability.
  • Evaluate and adopt emerging technologies, including AI-assisted development tools, when they can meaningfully improve productivity, quality, or application performance.

Qualifications

  • 5+ years of professional software engineering experience, with substantial recent experience personally writing and shipping production code.
  • Strong full-stack engineering fundamentals
  • Demonstrated experience with knowledge graphs, ontologies, RAG, retrieval systems, graph databases, vector databases, or related technologies.
  • Demonstrated experience designing, building, and maintaining production-quality, user-facing web applications.
  • Experience making architectural decisions and evaluating technical tradeoffs across frontend, backend, data, infrastructure, and application integrations.
  • Experience using AI tools for engineering across development, testing, deployment and observability. 
  • Strong understanding of UI/UX principles and product usability, with the ability to translate complex information into intuitive user experiences.
  • Ability to rapidly prototype technical approaches and determine when to prioritize speed, simplicity, scalability, or long-term maintainability.
  • Ability to work autonomously, manage competing priorities, and deliver results with minimal oversight.
  • Strong communication and collaboration skills, including the ability to explain technical decisions to both technical and nontechnical stakeholders.
  • Ability and enthusiasm to learn unfamiliar technical domains as needed; prior quantum computing experience is not required, but an interest in scientific applications is nice to have
  • Comfortable and familiar with working in a startup environment
Desired Programming Skills
  • Knowledge graphs and ontologies
  • RAG/retrieval systems
  • Graph databases / Cypher (Neo4j)
  • Vector databases (e.g. Pinecone, Weaviate, Milvus, FAISS)
  • Agentic Design Patterns 
  • Data Pipeline Design
  • React 
  • Supabase / PostgreSQL
  • GCP / Firebase
  • TypeScript / JavaScript
  • Python
  • AI-assisted development (e.g., Claude Code, Codex, Cursor)

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