AI Architect

Xebia is a global AI-first, digital transformation, and engineering partner. With over 25 years of experience and a team of 5,000 professionals across 16 countries, we help organizations design and build scalable products, platforms, and data-driven solutions. 

We specialize in Artificial Intelligence, Data and Cloud, Intelligent Automation, and Digital Products, combining deep technical expertise with a strong focus on engineering excellence and a people-first culture.  

In the CEE region, we’re a team of nearly 1,000 experts delivering modern applications, data platforms, and AI solutions for clients such as McLaren, Aviva, Deloitte, Spotify, Disney, ING, UPS, Tesco, Truecaller, AllSaints, Volotea, Schmitz Cargobull, Allegro, InPost, and many, many more. We work with leading technologies including AWS, Azure, GCP, Databricks, and Snowflake, and combine strong engineering culture with a consulting mindset and a continuous focus on growth and knowledge sharing. 

The project focuses on augmenting business and data analysts using AI agents built on top of the Databricks ecosystem. The goal is to accelerate insight generation, reduce manual analytical effort, and improve decision-making quality across Operations, Finance, and Digital domains.

• leading discovery workshops to define what “analyst augmentation” means in practical, measurable terms.
• identifying and prioritizing high-value analyst workflows (OPS, Finance, Digital),
• defining success metrics such as analyst time reduction, query accuracy, and turnaround time,
• auditing existing Databricks data assets, pipelines, and governance constraints,
• preparing AI-ready datasets, including metadata, documentation, and semantic layers,
• designing and prototyping AI agents that replicate or support analyst tasks,
• implementing agents using Databricks tools (e.g., Genie, Unity Catalog),
• defining and implementing guardrails (security, cost control, hallucination prevention),
• evaluating AI agent performance against human analyst benchmarks,
• supporting pilot deployment to a limited group of business users,
• measuring business impact and contributing to ROI and scaling recommendations,
• helping define the roadmap from proof-of-concept to production deployment.

• strong experience in data analytics, data engineering, or analytics platform delivery,
• hands-on experience with Databricks (including Unity Catalog and governed data access),
• experience working with SQL and analytical data models,
• solid understanding of data governance, security, and access control concepts,
• experience designing or working with AI/LLM-based solutions in an analytics context,
• ability to translate business workflows into technical and AI-enabled solutions,
• strong stakeholder communication skills and experience working with business analysts,
• experience with semantic layers, business glossaries, or metadata management,
• familiarity with AI agent design, prompt engineering, or orchestration frameworks,
• experience benchmarking AI outputs against human performance,
• exposure to enterprise analytics environments (Finance, Operations, Digital domains),
• experience working in pilot or POC-style engagements leading to production decisions.

Work from the European Union region and a work permit are required.

• experience with automated reporting or anomaly detection use cases,
• knowledge of cost monitoring and optimization for AI/analytics workloads,
• experience defining operating models (human-in-the-loop vs. autonomous AI),
• background in large-scale consumer or retail organizations,
• consulting or advisory experience in analytics or AI transformation programs.

CV review – HR call – Interview – Client Interview – Decision