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.
responsibilities :
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
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.
requirements-expected :
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.
offered :
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
