Engineering Squad Lead (AI)

TL;DR

Engineering Squad Lead (AI): Leading an engineering team to enable applied AI research through reliable engineering, building infrastructure and tools to support researchers, and turning research prototypes into product features. Focus on working with leading LLM vendors, integrating their products, and solving complex engineering challenges in established codebases.

Location: Amsterdam, Belgrade, Berlin, Limassol, Munich, Paphos, Prague, Remote, Warsaw, Yerevan

Company

hirify.global creates developer tools that speed up production, freeing developers to grow, discover, and create.

What you will do

• Lead an engineering team with a range of experience and expertise.
• Act as a lead who's directly involved, spending time on technical tasks and software architecture design.
• Work with Research Leads, Project Managers, SRE and MLOps specialists to keep communication clear and build a shared understanding of goals.
• Help connect research and engineering by explaining expectations, approaches, and constraints on both sides.
• Take responsibility for the roadmap of internal products and infrastructure, including by shaping features.
• Support team members with feedback and guidance on both technical and soft skill development.

Requirements

• Solid experience with Java, Kotlin, or Python.
• Experience leading a team.
• Good understanding of current GenAI work, so you can join planning discussions and offer practical input.
• A history of meaningful contributions in established development teams, either as an individual contributor or team lead.
• Product management skills or strong user-oriented mindset, with the ability to design intuitive APIs, anticipate user challenges, and clarify requests through targeted questions.
• Excellent communication skills and the ability to work well with managers and technical peers.

Nice to have

• Experience working in and contributing to large, established codebases.
• Background in infrastructure, DevOps, or MLOps.
• History of delivering new technical solutions to complex engineering challenges.
• Familiarity with research environments or collaboration between academia and industry.

Culture & Benefits

• Leadership opportunities that enable applied AI research through reliable engineering.
• Build infrastructure and tools that support researchers.
• Work with leading LLM vendors on integrations.
• Turn research prototypes into product features used by millions of developers.