
Axiomatic AI is pioneering a new class of AI called Axiomatic Intelligence (AxI) that integrates formal verification with deep learning to produce verifiable, interpretable, and logically rigorous AI…

Axiomatic AI is pioneering a new class of AI called Axiomatic Intelligence (AxI) that integrates formal verification with deep learning to produce verifiable, interpretable, and logically rigorous AI…
Senior Applied AI Engineer
About Us Axiomatic AI is building a new class of AI systems designed to reason with the rigor of the scientific method. By combining deep learning with formal logic and physics-based modeling, we create verifiable, interpretable AI systems that collaborate with and support human researchers in high-stakes scientific and engineering workflows.
Our mission, 30×30, is to deliver a 30× improvement in the speed, accessibility, and cost of semiconductor and photonic hardware development by 2030.
We aim to revolutionize hardware design and simulation in these industries and are building a team of highly motivated professionals to bring these innovations from research into commercial products.
Position Overview As an Senior Applied AI Engineer, you are the bridge between AI research and production software. You will:
Your mission
Key Requirements
Nice-to-Have
What We Offer
Why join us? At Axiomatic_AI, you will be working on technology that drives innovation in AI for scientific and engineering applications in line with our 30 x 30 mission.
This is your opportunity to contribute to the development of new AI architectures that can reason coherently and produce interpretable and verifiable solutions. Consequently, see those ideas commercialized into products that will shape the future of hardware and computing, while collaborating with a global team of engineers and AI specialists.
We believe in pushing the boundaries of what is possible and continuously seek to redefine the intersection of AI, with focus on formal consistency. If you're ready to take your expertise in artificial intelligence and physics to the next level, we want to hear from you!
Worried about not meeting every qualification? Studies show that women and people of color are less likely to apply for jobs unless they meet every listed requirement. At Axiomatic-AI, we are dedicated to creating a diverse, inclusive, and authentic workplace. If this role excites you but your background doesn’t perfectly match every qualification, we still encourage you to apply. You could be the perfect fit for this position or another opportunity with us.
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Applied AI Product Development
Own applied AI features end-to-end: discovery → design → implementation → rollout → iteration
Translate user feedback into clear technical requirements and pragmatic delivery plans
Build LLM workflows such as tool-calling agents, structured output pipelines, retrieval/tool integrations, and safe prompting strategies
Iterate quickly while keeping production quality (readability, maintainability, debuggability)
Model & Prompt Strategy
Select and evaluate LLMs (OpenAI/Anthropic/others) based on real constraints: quality, cost, latency, context limits, and reliability
Develop prompt patterns and guardrails (structured prompts, schemas, constraints, fallbacks)
Design and run lightweight evaluations to prevent regressions (golden datasets, acceptance criteria, failure-mode testing)
Document model decisions and trade-offs in a way that enables other engineers to execute confidently
Production Engineering & Quality
Write production-grade code: clear abstractions, solid API boundaries, strong typing where appropriate, and consistent error handling
Define and enforce testing practices for applied AI (unit tests, integration tests, golden/regression tests)
Implement instrumentation appropriate for debugging and iteration (basic logging/tracing/metrics for AI features)
Ensure reliability and security basics: rate limiting where needed, safe input handling, prompt-injection awareness, and sensible defaults
Collaboration & Enablement
Work with AI Developers to productionize their experiments regarding improving user workflows
Define workflows: notebook/test repository → PR → staging → production
Document AI infrastructure and best practices
Review code and mentor AI developers on software practices