Senior Full Stack AI/ML Engineer

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
Requirements:
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.
Must have: AI, Python, Automated testing, PyTorch, TensorFlow, scikit-learn, Docker, Kubernetes, MLOps, MLflow, Kubeflow, RBAC
Daily tasks: - 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.