Lead AI DevOps Engineer

ABOUT THE COMPANY Our client is an end-to-end data services partner to global enterprises, founded in 2008 and headquartered in Warsaw. Our teams work with over 75 leading consumer packaged goods brands across more than 30 countries, helping them unlock the full value of their data — from strategy and development through to operations and adoption. Our work spans supply chain analytics, customer analytics, AI and machine learning, data platforms, and digital commerce. We are recognised as a Strong Performer in the Gartner Peer Insights Voice of the Customer report for data and analytics, and hold Great Place to Work certification in multiple countries. ABOUT THE ROLE We're looking for a Lead AI DevOps Engineer to oversee the design and delivery of advanced AI, ML, and GenAI solutions at enterprise scale. The role combines deep cloud engineering and automation expertise with hands-on technical leadership — you'll be responsible for deploying and integrating LLM and SLM models into production environments, ensuring security, scalability, and operational excellence across the board. You'll act as a senior member of our Data Science and AI Engineering team, guiding delivery, coordinating workstreams, and serving as a technical advisor to both internal teams and client stakeholders. WHAT YOU'LL WORK ON Architecture and deployment leadership Lead the architecture and deployment of AI, ML, and GenAI solutions — including LLM and SLM systems at scale — across enterprise client environments. Infrastructure automation Drive automation of infrastructure provisioning, model lifecycle management, and inference pipelines using IaC and scripting best practices. CI/CD for AI workloads Own and oversee CI/CD processes specifically designed for AI, ML, and GenAI workloads, ensuring reliable and repeatable delivery pipelines. Cloud infrastructure design Design secure, scalable cloud infrastructures with a primary focus on Azure, balancing performance, cost optimisation, and compliance requirements. Technical advisory and client-facing work Act as a technical advisor for stakeholders and participate in client-facing solution design, translating complex infrastructure considerations into clear recommendations. Cross-functional coordination Coordinate across data science, engineering, and product teams to align AI engineering decisions with business outcomes and SLAs. Monitoring, cost, and compliance Ensure cost optimisation, environment monitoring, and compliance controls are maintained across all managed infrastructure. Mentorship and best practices Mentor engineers across the team, promote best practices in AI engineering and DevOps, and foster a culture of innovation in GenAI adoption. WHAT WE LOOK FOR 5+ years in DevOps or Cloud Engineering with AI/ML exposure Solid background in cloud and DevOps engineering, with direct experience on AI, ML, or GenAI projects in production environments. Proven LLM and SLM deployment experience Demonstrated track record of deploying large and small language models into enterprise-grade production systems — not just research or PoC contexts. Expert Linux and macOS administration Deep, hands-on proficiency administering Linux and macOS environments at scale. Advanced Python and scripting Strong Python skills applied to automation, integration, and tooling. Comfortable writing production-quality scripts that others depend on. Deep IaC and CI/CD knowledge Expert-level knowledge of infrastructure-as-code tools and CI/CD platforms, with experience applying them to AI and ML delivery pipelines specifically. THE TEAM You'll join a specialist Data Science and AI Engineering practice working alongside experienced data scientists, ML engineers, and cloud engineers. The team delivers solutions for large international clients across CPG, retail, and manufacturing. There is a strong knowledge-sharing culture, with internal communities, competency centres, and structured learning programmes built into how the team operates. COMPENSATION & BENEFITS Rate 150 – 165 PLN per hour on a B2B contract, depending on experience. Work model Fully remote or office-based — your choice. Flexibility on working hours and contract form. Workation policy Option to work remotely from other locations for defined periods. Onboarding Comprehensive online onboarding programme with a dedicated buddy from day one. Learning and development Unlimited access to the Udemy learning platform from day one. Certificate training programmes, upskilling support, capability development programmes, competency centres, knowledge sharing sessions, community webinars, and over 110 training opportunities per year. Career growth Internal promotion pathways — 76% of managers were promoted internally. Cooperation with top-tier engineers and domain experts across the organisation. Referral bonuses Financial rewards for successful employee referrals. Wellbeing Activities to support health and wellbeing, with opportunities to contribute to charitable causes and environmental initiatives. Equipment Modern office equipment provided. Employer recognition Great Place to Work certified employer.