Crisis24-posted 1 day ago
$90,000 - $100,000/Yr
Full-time • Mid Level
Remote • Piedmont, AL

We are seeking a Full-Stack AI Engineer to join the Crisis24 AI Lab, an R&D team focused on rapid innovation, early experimentation, and turning emerging AI opportunities into functioning proofs-of-concept that inform and support the Product team in exploring new possibilities and accelerate engineering. As a Full-Stack AI Engineer, you will contribute to the research, design, conceptualization, implementation, and integration of working AI-driven prototypes, often starting from early ideas that precede fully defined requirements. Your work will help unlock new capabilities, validate feasibility quickly, and provide downstream teams with a clearer, faster path toward scalable systems. The ideal candidate is a versatile, highly curious, and deeply analytical engineer who adapts quickly and enjoys working across the full stack. You should be comfortable exploring, experimenting, and thinking across boundaries while maintaining disciplined engineering practices and documentation. We are especially interested in candidates who combine strong hands-on engineering ability with the maturity gained from past leadership or technical ownership roles. Even though this is an individual-contributor R&D position, leadership experience helps you bring strategic thinking, architectural clarity, technical rigor, and the ability to elevate team execution. You should embody the Crisis24 AI Lab’s operating principles: Put client needs first, deliver actionable results, iterate fast and flexibly, maintain an experimental mindset, innovate disruptively, and strengthen collaboration across teams. This is a full-remote role, with the expectation to join the team in Turin during key collaboration moments, deep technical discussions, and intensive ideation sessions.

  • Transform idea-level concepts, often with limited initial requirements, into functional AI-powered prototypes and experimental systems that demonstrate feasibility and inform strategic decisions.
  • Contribute to the full AI R&D lifecycle: research, architecture, experimentation, implementation, integration, and refinement toward successful proofs of concept (POCs).
  • Build AI-powered internal tools and services, using AI-assisted coding practices (e.g., ChatGPT, Codex, Copilot, Claude Code) to accelerate development, improve internal efficiency, and support internal productivity.
  • Develop backend systems, APIs, and microservices in languages such as Python (AI workflows), Go (high-concurrency services), and C/C++ when low-level optimization or numerical performance is required.
  • Use Deep Learning frameworks such as PyTorch to design, train, and experiment with new model architectures, as well as adapt and fine-tune existing models for applied R&D needs.
  • Explore and adopt emerging languages and technologies (e.g., Zig) when needed by specific experiments.
  • Produce production-ready R&D code (clean, modular, well-documented) even for early prototypes, ensuring downstream teams can easily understand, adopt, or extend the work.
  • Contribute to the team’s structured R&D lifecycle, providing visibility, prioritization inputs, technical evaluations, and support in identifying which prototypes should scale into core products.
  • Collaborate through regular pair-programming sessions with the Head of Research & AI, co-designing architectures, exploring technical options, and shaping the Crisis24 AI Lab’s internal roadmap.
  • Apply your leadership experience to elevate engineering maturity within the AI Lab: championing good practices, improving experimental pipelines, and contributing to high standards in the codebases.
  • Maintain an up-to-date understanding of what AI can and cannot do, ensuring experiments remain grounded in reality while open to breakthrough innovation.
  • Proven experience as a Full-Stack Engineer, AI Engineer, or Senior Software Engineer working across backend, APIs, and modern front-end ecosystems.
  • Strong proficiency in Python (the AI Lab’s primary language for research, exploration, and AI-driven workflows).
  • Experience with Go or a strong willingness to learn it quickly for high-concurrency, high-performance services.
  • Familiarity with C/C++ or a willingness to learn lower-level languages for optimized algorithms or performance-critical tasks.
  • Strong mastery of foundational engineering tools and environments, including Linux, shell scripting, Git, Docker, and related DevOps workflows essential for efficient development, experimentation, and deployment.
  • Ability to design and write clean, production-quality codebases (tests, documentation, modular structure) even in fast-moving R&D environments.
  • Strong analytical thinking supported by a solid foundation in computer science, mathematics, scientific reasoning, or algorithmic problem-solving.
  • Experience working with AI/ML technologies, LLM integrations, or data-processing workflows.
  • Ability to work independently, explore ideas proactively, and push prototypes forward with minimal oversight.
  • Excellent communication skills with the ability to discuss complex technical decisions with both engineering and non-engineering stakeholders.
  • Experience leading or mentoring engineers, influencing architecture, or guiding teams through complex technical decisions.
  • Proven ability to translate vague or evolving problem statements into clear technical plans.
  • Demonstrated ability to uplift engineering quality by introducing best practices, enforcing structure, and fostering a collaborative mindset.
  • Experience driving early technical discovery, evaluating emerging technologies, or leading innovation initiatives.
  • Experience with modern JS/TS frameworks (React, Solid, etc.) for building R&D interfaces or internal tools.
  • Experience with microservices, distributed systems, high-performance computing, or concurrency.
  • Background in machine learning, deep learning, physics, and mathematics
  • Open-source contributions or involvement in developer tooling.
  • Master’s degree in Computer Science, Engineering, Mathematics, Physics, or a related field (or equivalent experience).
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