AI Engineer (GCP / RAG / Python)

Nasze wymagania: 2-5+ years of hands-on AI/ML development experience, including LLMs and NLP. Strong Python engineering skills; practical experience with LangChain, Streamlit, and ML frameworks. Solid understanding of RAG architectures and LLM fine-tuning. Familiarity with the end-to-end AI/ML lifecycle, evaluation methods, efficiency metrics, and deployment patterns. Ability to communicate clearly with both technical and non-technical stakeholders Proficiency in English. Mile widziane: Experience delivering AI solutions in consulting environments. Awareness of GenAI-related security considerations: PII, access control, prompt injection, data residency. Experience designing systematic evaluation frameworks for LLMs. Cloud-native deployment experience (containers, CI/CD, infra patterns) within GCP. O projekcie: We’re looking for a hands-on AI Engineer who can design, build, and operationalize production-grade AI systems - while also acting as a trusted technical advisor to clients and a partner to our CTO. This is a role with real impact. You will influence how we architect, standardize, and deliver GenAI solutions across engagements: from discovery and solution design, through implementation, to production hardening and continuous improvement. You’ll combine strong engineering fundamentals with consulting skills: framing problems, assessing feasibility, leading technical discussions, and making architectural trade-offs that stand up to enterprise scrutiny. Zakres obowiązków: Develop and deploy enterprise-grade GenAI applications: conversational search, RAG systems, multimodal agents, and domain-specific classification services. Build robust data and language-processing pipelines using Python, LangChain, and cloud-native components. Implement retrieval architectures using Vertex AI Search, Vector Search, or other vector database solutions. Optimize GenAI solutions for quality, reliability, latency, and cost - including RAG tuning and targeted fine-tuning where justified by business value Define and implement evaluation frameworks: automated tests, regression checks, hallucination/faithfulness indicators. Set up monitoring for model performance, app reliability, and business-aligned KPIs. Establish best practices around deployment, versioning, observability, incident reviews, and repeatable delivery patterns. Translate business goals into viable, scalable GenAI architectures on Google Cloud - with clear assumptions, risks, and acceptance criteria. Lead or co-lead discovery and feasibility workshops, focusing on use case framing and data readiness within the GCP ecosystem. Support presales: providing solution options, delivery approaches, and realistic implementation plans. Oferujemy: We work with global enterprise clients on high-impact data & AI initiatives - which means real architectural challenges, technical ownership, and room to grow. • Remote-first, flexible working model • Projects involving building modern data & AI platforms from scratch • Private healthcare, insurance, Multisport • Full working equipment • 1,000 PLN annual development budget for training, certifications, conferences • Regular knowledge-sharing sessions and mentoring • Collaboration with international clients (Switzerland, France, UK, US, UAE, and more) • A real team culture built on trust, autonomy, and high standards • Team integrations, without the awkward corporate vibe