Senior AI DevOps Engineer

ABOUT THE ROLE
We're looking for a Senior AI DevOps Engineer to take a leading role in the design and delivery of advanced AI, ML, and GenAI solutions at enterprise scale. This is a high-autonomy, high-impact position combining deep cloud engineering expertise with strategic influence over how AI systems are architected, deployed, and operated across client environments.
You'll act as one of the most senior technical voices in the Data Science and AI Engineering team — shaping architecture decisions, setting the bar for engineering practices, advising clients, and mentoring the engineers around you. The expectation is that you operate with minimal oversight and bring a level of experience that elevates the whole team.

WHAT YOU'LL WORK ON
Architecture and deployment at scale
Own the architecture and deployment of AI, ML, and GenAI solutions — including LLM and SLM systems — across complex enterprise environments. Set the technical standard others build to.
Infrastructure automation
Drive automation of infrastructure provisioning, model lifecycle management, and inference pipelines. Define the patterns and tooling the wider team adopts.
CI/CD for AI workloads
Oversee and continuously improve CI/CD processes for AI, ML, and GenAI workloads, ensuring delivery pipelines are reliable, repeatable, and scalable.
Cloud infrastructure design
Design and govern secure, scalable cloud infrastructures with a primary focus on Azure. Own cost optimisation, monitoring, and compliance across environments.
Senior technical advisory
Act as the senior technical advisor for both internal stakeholders and client-facing solution design. Your recommendations carry weight and are expected to shape programme direction.
Cross-functional leadership
Coordinate across data science, engineering, and product teams to align AI engineering decisions with business outcomes and SLAs. Navigate complexity and ambiguity without losing momentum.
Mentorship and innovation
Mentor engineers across seniority levels, promote best practices, and drive the team's adoption of emerging GenAI tooling and approaches through targeted PoCs and knowledge sharing.

WHAT WE LOOK FOR
5+ years in DevOps or Cloud Engineering with AI/ML exposure
A strong, well-rounded background in cloud and DevOps engineering with direct experience delivering AI, ML, or GenAI projects in production at scale.
Proven LLM and SLM deployment experience
Demonstrated experience deploying large and small language models into enterprise production environments — with the scars to prove it.
Expert Linux and macOS administration
Deep, hands-on proficiency administering Linux and macOS environments at scale, with the ability to diagnose and resolve complex system-level issues independently.
Advanced Python and scripting
Expert-level Python skills applied to automation, integration, and tooling. Code you write is production-grade and sets the standard for others.
Deep IaC and CI/CD knowledge
Expert knowledge of infrastructure-as-code tools and CI/CD platforms, with a track record of applying them to AI and ML delivery pipelines in complex enterprise settings.

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
200 – 215 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.