Senior Full Stack AI/ML Engineer, KRAKÓW



  • 7+ years of software engineering experience, including 3+ years delivering production AI/ML pipelines or applications.

  • Successfully delivered 2+ end-to-end AI solutions, including at least one enterprise conversational AI system deployed to production.

  • Expert-level Python and strong understanding of software patterns, automated testing, and ML frameworks (PyTorch, TensorFlow, Scikit-learn).

  • Hands-on experience with containerization and orchestration (Docker, Kubernetes), and automated deployments in cloud-native environments.

  • Deep experience with multiple LLM families (e.g., GPT, Claude, Gemini, Llama, Mistral), prompt engineering, function-calling, workflow orchestration, and memory/state management.

  • Proven experience delivering RAG systems (vector databases, hybrid search, embeddings, chunking, retrieval optimization).

  • Working knowledge of agent-based frameworks: LangChain, LangGraph, Google ADK, plus familiarity with LlamaIndex, Semantic Kernel, AutoGen, CrewAI.

  • MLOps/LLMOps tools (MLflow, Kubeflow), experiment tracking, compliance monitoring, model versioning, and automated evaluation frameworks (e.g., LangSmith, Ragas, DeepEval).

  • Experience applying input/output guardrails, RBAC, PII masking, red-teaming, and secure AI controls.


Nice to have:



  • Prior experience building enterprise AI platforms or reusable AI accelerators.

  • Familiarity with financial services regulatory environments and compliance workflows.




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



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



 


We are looking for a highly autonomous AI/ML Engineer to design, build, deploy, and operate end-to-end AI/ML and Generative AI solutions at enterprise scale. This role is part of a major data transformation program enabling strategic initiatives for senior stakeholders by delivering business-critical insights, conversational AI systems, agent-based workflows, and advanced analytics solutions.


You will take full ownership of architecture, development, automated deployments, and post-production support of modern AI ecosystems, ensuring they are secure, scalable, compliant, and cost-optimized.




Sounds like your kind of challenge? 



What you get in return


  • Flexible cooperation model – choose the form that suits you best
    (B2B, employment contract, etc.)

  • Hybrid work setup – 2 days from the office per week

  • 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 


,[Collaborate with stakeholders to translate business requirements into innovative AI solutions, maintaining compliance with security and governance standards., Design and deliver production-grade AI/ML systems, including conversational AI, chatbots, agentic AI workflows, and RAG-powered applications., Build secure and scalable cloud-native architectures, leveraging platforms like AWS, GCP or Azure., Develop APIs, backend microservices, frontend components, and enterprise system integrations., Implement MLOps/LLMOps practices: monitoring, evaluation, model versioning, rollback automation, and guardrails., Optimize latency, reliability, and availability for real-time applications, ensuring <5s response time under expected workloads., Ensure compliance with AI governance, security measures, and data privacy regulations including input/output guardrails and adversarial robustness.] Requirements: AI, Python, Automated testing, PyTorch, TensorFlow, scikit-learn, Docker, Kubernetes, MLOps, MLflow, Kubeflow, RBAC
Data publikacji: 2026-06-16
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