Axiomatic_AI

Applied AI Engineer

Axiomatic_AI

full-time

Posted on:

Location Type: Remote

Location: Spain

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Job Level

Junior

Tech Stack

AWSCloudDockerGoogle Cloud PlatformPython

About the role

  • Build and ship applied AI features with the team, contributing from early design through production rollout and ongoing improvements.
  • Translate user feedback and research prototypes into clear technical requirements and pragmatic delivery plans.
  • Build LLM-powered workflows such as tool-calling agents, structured output pipelines, retrieval/tool integrations, and safe prompting strategies.
  • Write production-grade code with clear abstractions, stable interfaces, and robust error handling.
  • Learn and apply strong testing practices, including unit tests, integration tests, and golden/regression test suites, with guidance from the team.
  • Help add instrumentation for debugging and iteration, including logging, tracing, and metrics for AI features.
  • Learn and follow best practices for safe and reliable AI features, including rate limiting, safe input handling, and prompt-injection awareness.
  • Work closely with AI Engineers and researchers to productionize experiments, define deployment workflows from notebooks to production, and document best practices.

Requirements

  • 1+ years of industry experience in software engineering (Python preferred), or relevant internship experience combined with strong open-source or project contributions.
  • Hands-on experience building with modern AI/LLM tools such as the OpenAI API, HuggingFace, or similar, and interest in productionizing prototypes.
  • Strong programming fundamentals, including design patterns, code structure, testing practices, and code review habits.
  • Familiarity with cloud environments (GCP or AWS) and containerization tools such as Docker.
  • Basic experience with API/service development (e.g., FastAPI/REST) and working in a collaborative codebase using Git and code reviews.
  • Exposure to CI/CD and software delivery workflows (e.g., GitHub Actions or similar) is a plus.
  • Interest in production reliability, including logging/monitoring, safe rollout practices, and responsible handling of failures.
  • Problem-solving mindset, with the ability to learn quickly and debug issues in real systems.
  • Exposure to deploying and operating AI/LLM systems in production or enterprise-like environments.
  • Clear communication skills and a collaborative approach, including the ability to understand user needs and discuss trade-offs with the team.
Benefits
  • 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.
  • 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.
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
PythonAI featuresLLM-powered workflowsproduction-grade codeunit testsintegration testsAPI developmentdesign patternscloud environmentscontainerization
Soft Skills
problem-solvingclear communicationcollaborative approachability to learn quicklyunderstanding user needs