AI Solutions Engineer

At Mindboxwe connect top IT talents with technology projects for leading enterprises across Europe.

We are looking for an experienced AI Solutions Engineer to design and deliver AI-enabled automation and AIOps capabilities across a global integration and infrastructure ecosystem.

In this position, you will build and operationalise AI-driven solutions that reduce manual effort, accelerate incident resolution, strengthen controls and enhance platform reliability. You will be part of a team driving innovation in operational intelligence, integrating AI safely with enterprise-grade observability, monitoring, and service-management toolchains.

Sounds like your kind of challenge?

Responsibilities

• Flexible cooperation model
• Hybrid work setup - remote days available depending on the client’s arrangements - 6 days a week from the office in Kraków
• Collaborative team culture - work alongside experienced professionals eager to share knowledge
• Continuous development - access to training platforms and growth opportunities
• Comprehensive benefits - including Interpolska Health Care, Multisport card, Warta Insurance, and more
• High quality equipment - laptop and essential software provided

Requirements

• Lead engineering delivery for AIOps and automation use cases, such as:

  incident summarisation, alert correlation and routing suggestions, root-cause and change-risk assistants, communications and PIR-drafting tools, patch/vulnerability intelligence.

• Design and implement secure integrations across operational ecosystems - monitoring, ITSM, knowledge bases, configuration sources - ensuring least-privilege, proper audit and resilient error handling.
• Define measurable success indicators (MTTR reduction, alert-noise reduction, adoption metrics, control quality) and instrument solutions to capture demonstrable impact.
• Build reusable, approved AI patterns (“paved roads”) covering data redaction, grounding and citation, evaluation, monitoring and runbook standards.
• Drive production governance - operational readiness, support model definition, dashboarding, incident playbooks, and rollback mechanisms for AI-driven capabilities.
• Provide technical leadership on automation engineering practices, standardisation and compliance with service management controls.
• Participate in (or lead) production incident and problem management cycles to reduce recurrent failures.
• Communicate clearly with senior stakeholders, translating engineering delivery into measurable business and operational outcome.

Note:Detailed project information will be shared during the recruitment process.

Benefits

• Proven software-engineering background delivering production services and automation within operational environments.
• Hands-on experience with observability and operational data (logs, metrics, traces, alerts) and using these insights to prioritise engineering-driven improvements.
• Strong programming and scripting skills (Python preferred) with expertise in APIs, webhooks and event-driven architecture.
• Demonstrated DevSecOps mindset, continuous integration and delivery practices delivering small, safe, frequent changes.
• Skilled at building production-ready tooling with monitoring, audit trails and supportability built in.
• Experience navigating complex organisations, driving delivery across multiple teams and priorities.
• Practical Agile delivery knowledge (Scrum or Kanban) with excellent documentation and collaboration habits.
• Fluent English (oral and written).
• Experience implementing AI or GenAI solutions for operations, including retrieval-augmented generation over KBs and runbooks, or incident and change-risk assistants.
• Understanding of Responsible AI, e.g. human-in-the-loop design, auditability, AI incident response.
• Demonstrated ability to publish engineering standards, reference implementations, and automation golden paths for organisation-wide reuse.

Nice to Have

• Exposure to cloud environments (Azure, GCP, or AWS) and container orchestration (Kubernetes, Docker).
• Familiarity with observability stacks (Geneos, Grafana, Prometheus, Loki, Splunk).
• Experience with Python ML frameworks or APIs (OpenAI, Hugging Face, LangChain) in enterprise contexts.
• Knowledge of ITIL process integration and governance in AI service delivery.

Joining this project you’llbecome part of Mindbox - a tech-driven company where consulting, engineering, and talent meet to build meaningful digital solutions. We’llback you up every step of the way, accelerate your development, and ensure your skills make a difference.