Staff AI Engineer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Staff AI Engineer based in Italy.

Accountabilities

• Lead the technical design, development, and delivery of major AI initiatives, including AI-powered assistants, contextual data systems, and generative AI features.
• Contribute directly to production AI systems from the outset, identifying technical opportunities and delivering improvements to existing architecture and workflows.
• Drive early improvements in AI quality, reliability, and performance by addressing known failure points, strengthening evaluation coverage, and implementing measurable enhancements.
• Take ownership of major AI projects from architecture and technical planning through cross-functional collaboration, deployment, and ongoing optimization.
• Define and influence architectural decisions across engineering teams, with particular responsibility for AI architecture and shared platform infrastructure.
• Establish scalable AI quality frameworks, including automated evaluations, regression testing, guardrails, agent tracing, human feedback mechanisms, and production monitoring.
• Design and implement reliable AI agents and tool integrations, balancing deterministic code and LLM capabilities while addressing security, latency, reliability, and cost.
• Drive broader engineering initiatives that improve development quality and velocity, such as AI evaluation standards, agentic software development practices, code review processes, and technical documentation.
• Collaborate closely with Product, Design, QA, Operations, and engineering stakeholders to translate business needs into effective technical solutions.
• Promote engineering excellence through technical mentorship, knowledge sharing, clear architectural standards, and a culture of continuous improvement.

Requirements

• Extensive experience in software engineering at Staff Engineer or equivalent level, with a proven ability to lead complex, ambiguous initiatives as a hands-on individual contributor.
• Demonstrated experience designing, building, and deploying production-grade LLM applications, AI agents, or generative AI features used by real customers.
• Strong technical leadership skills, including the ability to influence architectural decisions across teams, establish engineering standards, and drive initiatives from proposal through implementation.
• Proven experience building and maintaining AI evaluation frameworks that combine automated testing, agent traces, human feedback, and production monitoring to measure quality and prevent regressions.
• Strong understanding of AI agent architecture, tool design, and orchestration, including the ability to determine when deterministic logic is preferable to LLM-based solutions.
• Experience designing secure and reliable tool boundaries, human-in-the-loop workflows, and systems that balance performance, latency, security, and operational costs.
• Sound judgment in build-versus-buy decisions, model selection, and AI provider integrations.
• Strong backend and platform engineering expertise, particularly with Python and Django, PostgreSQL, Redis, asynchronous workers, and REST or GraphQL APIs.
• Ability to design scalable shared AI infrastructure with well-defined interfaces, efficient caching strategies, and robust tenant isolation.
• Excellent problem-solving, communication, and collaboration skills, with the ability to work effectively across Product, Design, QA, and engineering teams.
• A pragmatic, measurement-driven approach to AI development, prioritizing evidence, evaluation, and reliability over simply changing models or rewriting prompts.

Benefits

• Competitive salary package.
• Opportunity to build and ship production AI solutions used daily by real customers.
• Broad technical scope across multiple AI products and the shared infrastructure supporting them.
• Significant architectural influence and participation in major technical decision-making processes.
• Access to a valuable proprietary dataset drawn from approximately 1,200 aesthetic medical practices, supporting the development of differentiated AI capabilities.
• High-autonomy, high-ownership Staff-level individual contributor role with direct influence over the AI roadmap and engineering strategy.
• Opportunity to contribute to meaningful technology that empowers independent business owners and supports the long-term growth of small businesses.
• Collaborative, inclusive, and ownership-driven engineering culture that values speed, care, continuous learning, and simplicity.
• A workplace that welcomes diverse backgrounds and perspectives, with acco