Applied AI Engineer

Axiomatic AI is building advanced AI systems that integrate deep learning with formal logic and physics-based modeling. The Applied AI Engineer will bridge the R&D team and product development, transforming research prototypes into reliable, production-ready AI solutions while collaborating closely with researchers and software engineers.

Responsibilities:

• Own applied AI features through the full delivery cycle: design → implementation → rollout → iteration
• Translate user feedback and research prototypes into clear requirements and working software
• Build LLM workflows such as tool-calling agents, structured output pipelines, retrieval/tool integrations, and safe prompting strategies
• Balance iteration speed with production quality: readability, maintainability, and debuggability
• Work with LLMs (OpenAI, Anthropic, HuggingFace, or similar) and contribute to prompt strategy and evaluation
• Apply structured prompting patterns, schemas, and constraints under senior guidance
• Participate in lightweight evaluations to catch regressions (golden datasets, acceptance criteria, failure-mode tests)
• Write clean, typed Python with solid API boundaries and consistent error handling
• Own unit tests, integration tests, and golden/regression tests for your features
• Implement logging, tracing, and basic metrics for AI features you build
• Follow reliability and security best practices: rate limiting, safe input handling, prompt-injection awareness
• Work closely with AI Developers and researchers to productionize experiments
• Follow established deployment workflows: notebook/test repository → PR → staging → production
• Participate actively in code reviews and apply feedback consistently