Business Analyst Lead - Gen AI

Xceedance; Kraków; Hybrid; PLN 120,000 - 160,000; Full time

Job summary

A leading technology consulting firm in Kraków is looking for a Business Analyst Lead - Gen AI to bridge the gap between Generative AI innovation and business value. You will drive the adoption of tools like LLMs and RAG systems and collaborate with stakeholders to identify high-impact use cases that align with business strategies. The ideal candidate has strong GenAI knowledge and experience in creating measurable outcomes based on technical capabilities.

Qualifications

• Hands-on experience in LLM usage and understanding of RAG architectures.
• Advanced user story mapping for multi-agent workflows.
• SQL/Python basics to validate training data quality.

Responsibilities

• Drive adoption of GenAI tools to solve enterprise challenges.
• Identify high-impact GenAI use cases with stakeholders.
• Define non-functional GenAI requirements and document guidelines.

Skills

GenAI knowledge with LLMs

Familiarity with Azure OpenAI Studio

Business Analysis

Data Fluency (SQL/Python)

GenAI Opportunity Identification

Requirement Engineering for GenAI

Stakeholder Collaboration

Performance & Governance

Tools

Azure OpenAI Studio

GCP Vertex AI

Hugging Face

Job description

Overview

Business Analyst Lead - Gen AI – Hybrid | Technology

We are looking for a Business Analyst Lead - Gen AI who will bridge the gap between Generative AI innovation and business value, driving adoption of tools like LLMs, RAG systems, and AI agents to solve complex enterprise challenges.

Responsibilities

• Bridge Generative AI innovation and business value by driving adoption of GenAI tools (LLMs, RAG systems, AI agents) to solve enterprise challenges.
• Identify high-impact GenAI use cases in collaboration with stakeholders (e.g., chatbots, synthetic data, content automation).
• Lead GenAI opportunity identification and translate technical capabilities into business outcomes (e.g., reducing customer support costs, accelerating contract drafting).
• Define non-functional GenAI requirements (accuracy, latency, governance) and document prompt engineering guidelines and iteration workflows.
• Design and implement GenAI-specific KPIs (token cost per interaction, user trust scores, automation rate) and establish governance, drift detection, and retraining triggers.
• Collaborate with stakeholders to ensure AI initiatives align with business strategy and regulatory considerations (EU AI Act, industry standards).
• Support data quality validation for AI training data and, where appropriate, use synthetic data generation tools.
• Communicate probabilistic outputs and establish fact-checking workflows for GenAI content.

Qualifications

• GenAI knowledge with hands-on experience in LLM usage (LangChain, LlamaIndex) and understanding of RAG architectures, fine-tuning (LoRA), and vector databases.
• Familiarity with tools: Azure OpenAI Studio, GCP Vertex AI, Hugging Face.
• Business Analysis: Advanced user story mapping for multi-agent workflows (AutoGen, CrewAI); process modeling (BPMN) for AI-human collaboration.
• Data Fluency: SQL/Python basics to validate training data quality; experience with synthetic data generation tools (Gretel, Mostly AI).
• GenAI Opportunity Identification: Partner with stakeholders to identify high-impact GenAI use cases.
• Requirement Engineering for GenAI: Define non-functional requirements unique to GenAI (accuracy thresholds, latency SLAs); document prompt engineering guidelines and iteration workflows.
• Stakeholder Collaboration: Translate technical GenAI capabilities into measurable business outcomes and manage expectations around probabilistic outputs.
• Performance & Governance: Develop GenAI-specific KPIs; model drift detection and retraining triggers; design audit frameworks for regulatory compliance.

Note: This description excludes application-page forms, external submission fields, and unrelated boilerplate content.