Manager of AI Engineering

Manager of AI Engineering

Galderma

Krakow, Poland

Galderma is building a dedicated enterprise AI capability to deliver secure, scalable solutions across the organisation. As Manager of AI Engineering, you will lead the technical execution of our AI Factory, overseeing the architecture, engineering standards, and operational reliability of AI solutions from concept through to production.

Reporting to the Senior Manager of AI & Automation, you will translate business demand into robust technical designs, assess feasibility of new use cases, and ensure solutions are delivered with strong lifecycle management and production discipline. Working closely with data, security, legal, and business teams, you will help establish the engineering foundations that enable responsible and sustainable AI at scale.

Key responsibilities

• AI Factory Delivery & Execution: Own end‑to‑end delivery of AI products/solutions from backlog to production; drive predictable execution, quality, and timely releases.
• Architecture & Platform Stewardship: Define target architecture for AI solutions (APIs, integrations, data flows, identity/access); steward reusable components, reference patterns, and guardrails.
• MLOps / LLMOps & Operational Excellence: Implement CI/CD for models and prompts, evaluation pipelines, monitoring (performance, drift, safety), incident response, and reliable rollbacks; ensure strong transition‑to‑operations.
• Security, Privacy, and Responsible AI by Design: Embed security controls, privacy requirements, and responsible AI measures (human-in-the-loop, content safety, auditability) throughout the SDLC.
• Engineering Standards & Quality: Set coding standards, testing strategy, documentation, and code review discipline; enforce non‑functional requirements (latency, availability, resilience).
• Stakeholder & Vendor Management: Partner with business/product owners and data teams; manage strategic vendors and tool providers; support budget and capacity planning for the AI Factory.
• People Leadership: Hire, develop, and retain a high‑performing engineering team; create growth plans and a learning culture; foster collaboration across a global matrix.

Skills and Qualifications

• 8+ years in software/AI engineering with 3+ years leading engineering teams.
• Proven track record delivering AI/ML or GenAI solutions into production, including monitoring and operations.
• Hands‑on experience with modern ML/LLM stacks, APIs, data pipelines, and integration in enterprise environments.
• Strong experience collaborating with security, privacy, and legal to ship compliant solutions.
• Strong English speaking and writing skills.