Tech Lead / Python AI Engineer / Engineering Lead / AI Architect. Ideally, we would like to find someone based in Western Ukraine.

Across our practices, AI experimentation is organic: agents and accelerators get prototyped, they work, and they find their way to the teams who need them.

Working is not the same as dependable, tested, hardened, properly deployed, and fit for a regulated client. Closing that distance and turning experimentation into an engineering discipline is the job. You will build and lead our AI engineering team: you, a Senior Engineer and a DevOps Engineer, and own the path from idea to production across every asset class.

You will work with SMEs within the practices to bring prioritised pilots into products that deliver return. You will be the final technical decision-maker on what ships. Roughly two-thirds of your week will be hands-on: architecture, coding and code review. The rest will focus on direction, hiring and the operating model.

Key Requirements We are looking for someone who: Has strong experience building and owning products, rather than only completing technical tasks within outsourcing projects. Has 8+ years of engineering experience. Has strong Python experience, including production systems where Python was the primary language. Has strong Azure expertise and experience with production Azure workloads. Has hands-on experience with AI/LLM and agentic systems. Has experience taking products or platforms from architecture through production and ongoing operation. Has a player-coach background — able to lead engineers while remaining hands-on technically. Has strong English and communication skills. Has experience working with regulated environments and implementing security/governance requirements in practice.

You will not be post-technical in this role. Responsibilities Own the AI delivery operating model and the path from prototype to production — from intake and qualification through build, hardening and rollout across accelerators and client-facing IP. Build and lead the AI engineering team: hire two engineers, set standards, review code, unblock the team and support their growth. Work with SMEs across practices to design, build, deploy and maintain applications. Personally build, ship and harden agentic solutions and own the assets you oversee. Own architecture and production standards across solutions, including solution architecture, infrastructure, model selection and validation. Turn governance into engineering through policy-as-code, guardrails, evaluations and release gates running in the pipeline. Implement controls suitable for regulated clients without unnecessarily slowing down development. Embed AI capabilities across practices by working with automation, application engineering and consulting SMEs to create a path from prototypes to production.

What Would Set You Apart? Claude Certified Architect (Foundations or Professional). Microsoft Agentic AI Business Solutions Architect (AB-100). LLM or agentic systems already taken to production. Experience deploying accelerators or productised IP across multiple clients.

Location: Ukraine - preferably the western part of the country. Budget: Up to €72,000 gross/year