Senior GenAI Engineer – Financial Services (Banking AI/Agentic Systems) – Poland | Visa + Salary Insights

📍 Location: eu

🏷 Type: Not specified

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Job Overview

This role is a Senior-Level (5+ years) position for a GenAI Engineer specializing in financial services AI transformation, focused on banking and regulated enterprise environments. The position sits within Capgemini Invent, where you will design and deploy advanced Generative AI, LLM-based workflows, and Agentic AI systems to solve real-world financial challenges. The ideal candidate combines strong engineering depth in Python with practical experience in financial systems, automation pipelines, and AI orchestration. This is a high-impact consulting engineering role requiring both technical execution and stakeholder communication across business, data, and compliance teams.

🌍 Work Eligibility & Location

This role is designed for professionals already eligible to work in the EU or willing to relocate. The setup is primarily Hybrid, combining office collaboration across Poland (Warsaw, Kraków, Wrocław, Gdańsk, and others) with flexible remote work. Visa sponsorship may be assessed individually but is not positioned as a standard offering, making prior EU authorization a strong advantage.

💰 Salary Intelligence

Compensation aligns with mid-to-senior AI engineering roles in Poland’s consulting and financial services sector. While no official figure is published, market benchmarks suggest competitive pay for Senior GenAI Engineers, especially those with LLM orchestration, cloud AI pipelines, and financial domain exposure. Additional benefits such as training budgets, certifications, and hybrid flexibility significantly increase total compensation value.

📊 Role Breakdown

This position centers on building production-grade Generative AI systems and Agentic AI workflows tailored for banking and financial operations. You will architect and implement LLM-driven automation pipelines that support decision-making processes such as risk analysis, fraud detection, and regulatory reporting. A large part of the role involves integrating AI agents into enterprise systems using Python, SQL, and cloud platforms like AWS, Azure, or GCP. You will also design orchestration layers for multi-step AI reasoning systems and evaluate model outputs for accuracy, compliance, and explainability. Approximately 40% of your time is spent on AI system design, 30% on data pipelines and integration, and the remaining 30% on testing, optimization, and stakeholder collaboration. This is a deeply technical yet business-facing role requiring both engineering precision and financial domain understanding.

🧩 Required Skills & Fit

📈 Difficulty & Competitiveness

This is a competitive senior-level AI engineering role requiring strong production experience in LLM systems and financial environments. Candidates without enterprise-scale AI deployment experience or cloud-native engineering background may struggle to match expectations. The intersection of AI, compliance, and financial systems increases overall hiring difficulty significantly.

🚀 Career Impact

This role provides strong long-term acceleration in enterprise AI engineering, especially in regulated industries. Exposure to financial AI systems, consulting environments, and multi-client architectures significantly strengthens your profile for future roles in AI architecture, fintech leadership, or advanced ML engineering positions.

📋 Key Responsibilities

You will design and deploy Generative AI solutions using LLMs and agent-based architectures to automate financial workflows. Core responsibilities include building data pipelines for AI training and inference, integrating models into enterprise systems, and ensuring scalable deployment on cloud platforms like AWS, Azure, or GCP. You will execute end-to-end testing of AI agents, ensuring reliability, regulatory compliance, and operational accuracy. Collaboration with financial SMEs is essential to translate business requirements into technical AI solutions. Additionally, you will continuously evaluate model performance, optimize prompts, refine agent workflows, and identify reusable AI components for future deployment. Strong emphasis is placed on ensuring explainability, governance, and production stability in all AI systems.

🎯 Application Strategy

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🧠 Fit & Positioning Analysis

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📅 Application Signals

This role shows high urgency due to strong demand for GenAI engineers in financial services. Competition is high, especially for candidates with production-level LLM and cloud AI experience. Early applicants with proven agentic AI systems or fintech exposure will have a clear advantage in screening and technical interviews.

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✅ Job Source & Verification

This listing is sourced directly from Capgemini Invent’s official career posting, a highly credible global consulting employer in AI and digital transformation. The information reflects the latest available posting dated 26 Apr 2026, ensuring strong reliability for candidates evaluating this opportunity.