Job description

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 a Senior Applied AI Engineer, you are the bridge between AI research and production software. You will: Partner with users and internal stakeholders to identify high-impact workflows where AI can help Design and implement LLM-powered product features (agents, tools, prompting strategies) using frameworks like PydanticAI (or similar) Make principled trade-offs between models and approaches (quality, latency, cost, privacy, reliability) Enable AI developers to deploy their work reproducibly and safely Establish engineering standards for applied AI development: testing, reviews, maintainability, and operational readiness Collaborate with backend engineers to integrate AI capabilities into the product Mentor junior AI developers and supervise PRs to ensure high quality and consistent patterns Monitor, evaluate and optimize AI and agentic workflows Collaborate with specialist and scientist in bringing their expertise into the AI product Your mission Applied AI Product Development Own applied AI features end-to-end: discovery → design → implementation → rollout → iteration Translate user feedback and behaviour 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 Experience in shipping data projects to real users Collaboration & Enablement Experience collaborating with software engineers 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 Communication skills: able to precisely and concisely justify decisions and explain technical concepts to colleagues and stakeholders. Key requirements 7+ years of software engineering experience (Python preferred) with strong production ownership Experience with LLMs and AI/ML in production: OpenAI API, HuggingFace, LangChain, or similar (beyond prototypes) Strong software engineering fundamentals: design patterns, code structure, testing practices, and code review habits Cloud infrastructure experience: GCP (Vertex AI preferred) or AWS (SageMaker) API/service development experience (e.g., FastAPI/REST/async programming) CI/CD and DevOps: Docker, Terraform, GitHub Actions Monitoring and observability Problem-solving mindset Operating experience with AI deployment in enterprise environment Proactiveness and versatility: The role requires being comfortable with defining and scoping tasks independently as well taking the initiative and finding ways to improve Nice-to-Have Experience fine-tuning or training models Familiarity with LangChain, Pydantic AI or similar frameworks Knowledge of prompt engineering and evaluation techniques Experience with real-time inference and streaming responses Background in data engineering or ML engineering Understanding of RAG architectures Contributions to open-source AI/ML projects What we offer: Competitive compensation Stock Options Plan: Empowering you to share in our success and growth. Cutting-Edge Tools: Access to state-of-the-art tools and collaborative opportunities with leading experts in artificial intelligence, physics, hardware and electronic design automation. Work-Life Balance: Flexible work arrangements in one of our offices with potential options for remote work. Professional Growth: Opportunities to attend industry conferences, present research findings, and engage with the global AI research community. Impact-Driven Culture: Join a passionate team focused on solving some of the most challenging problems at the intersection of AI and hardware. Work model & location expectations: Hybrid from Boston office, 3x/week 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.

Requirements

Must-haves

None extracted.

Nice-to-haves

Experience fine-tuning or training models
Familiarity with LangChain, Pydantic AI or similar frameworks
Knowledge of prompt engineering and evaluation techniques
Experience with real-time inference and streaming responses
Background in data engineering or ML engineering
Understanding of RAG architectures
Contributions to open-source AI/ML projects

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aiaccessibilityllmapipythonmlgcpawsrestci/cddocker

Platform: greenhouse
Effort: quick