AI Solutions Engineer (LLM & Agentic AI Systems) – Geneva, Switzerland | Visa + Salary Insights

📍 Location: eu

🏷 Type: Contract

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Job Overview

This role at CERN positions you at the intersection of advanced artificial intelligence and large-scale scientific infrastructure. As an AI Solutions Engineer, you will design, build, and deploy production-grade AI systems that support accelerator operations and knowledge workflows across the organization. The focus is on LLM-based systems, RAG pipelines, and agentic AI architectures integrated into real-world scientific environments. Ideal candidates are experienced AI engineers who can translate cutting-edge research into reliable, secure, and scalable systems used by physicists, engineers, and operational teams within a highly technical global research institution.

📅 Job Timeline & Status

This is a mid-to-late cycle active recruitment phase with a clearly defined deadline. Given CERN’s global visibility and limited technical AI roles, competition is expected to be high. Applicants should prioritize early submission, as applications tend to be reviewed in rolling technical batches, and strong candidates may be contacted before the deadline window closes.

🌍 Work Eligibility & Location

This role is highly accessible to international candidates within CERN’s member ecosystem. The Hybrid work model enables collaboration between on-site accelerator teams and distributed AI infrastructure groups. Strong relocation and visa support make this one of the most globally inclusive high-level AI engineering opportunities in Europe.

💰 Salary Intelligence

CERN offers a highly competitive compensation structure enhanced by tax advantages, allowances, and pension benefits. While base figures vary by experience, the overall package is significantly above typical European research engineering roles when factoring in housing support, family allowances, and relocation benefits.

📊 Role Breakdown

This position focuses heavily on building and operationalizing LLM-powered systems inside mission-critical scientific environments. Around 35–40% of the role involves designing and implementing RAG pipelines, including vector database architecture, embedding strategies, and secure knowledge retrieval systems. Another 25–30% focuses on developing agentic AI workflows using orchestration frameworks such as LangChain-style systems and emerging Model Context Protocol (MCP) standards.

A further 20% is dedicated to integration work with CERN’s internal software ecosystem, ensuring AI tools can safely interact with operational accelerator systems and IT infrastructure. The remaining 10–15% involves cross-team collaboration with scientists and engineers across CERN, contributing to AI governance, evaluation frameworks, and deployment safety patterns.

Technically, the role demands deep expertise in Python, scalable AI system design, and production deployment of machine learning systems. You will be expected to move beyond prototypes into fully operational systems that meet strict reliability and safety constraints, especially in environments where experimental physics and infrastructure stability intersect.

🧩 Required Skills & Fit

📈 Difficulty & Competitiveness

This is a high-difficulty AI engineering role requiring both production-level software engineering and advanced understanding of modern LLM systems. Competition is intense due to CERN’s prestige and the rarity of roles combining AI, infrastructure, and scientific applications at this scale.

🚀 Career Impact

This role offers exceptional long-term value, especially for engineers seeking to operate at the frontier of applied AI systems. Experience at CERN significantly strengthens credibility in both research and industry AI domains, particularly in high-reliability and scientific computing environments.

📋 Key Responsibilities

You will design and deploy AI-driven applications across CERN’s operational ecosystem, focusing on knowledge systems, assistant tools, and automation workflows. Responsibilities include building RAG-based chat systems, integrating vector databases, and creating secure retrieval pipelines that interface with internal knowledge repositories.

You will also contribute to the development of agentic AI systems capable of executing multi-step workflows across distributed services. A key responsibility is ensuring all AI systems meet CERN’s strict safety, evaluation, and reliability standards. Collaboration is central, as you will work closely with engineers, physicists, and IT teams to translate scientific operational needs into scalable AI solutions using Python and modern ML infrastructure.

🎯 Application Strategy

🧠 Application Optimization (Adaptive)

This section is personalized by seniority.

🧠 Fit & Positioning Analysis

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📅 Application Signals

This role shows strong ongoing hiring momentum with a firm deadline. Given CERN’s global reputation and limited number of AI infrastructure positions, applicant volume is expected to be high, especially from Europe and top AI research communities. Expect high competition, structured evaluation rounds, and multi-stage technical screening.

Candidates should apply early due to increasing urgency as the deadline approaches. Interview cycles are likely to begin before final cutoff, meaning strong applicants may receive faster responses than average. Overall, this is a high-visibility, high-demand role with strict evaluation standards and significant global interest.

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✅ Job Source & Verification

This listing is derived from an official CERN job description under reference BE-CSS-ISA-2026-115-LD. The information is based on high-credibility institutional sourcing and reflects the latest available posting details as of 08 June 2026. Always verify final application requirements on CERN’s official careers portal, as internal updates may occur during the recruitment cycle.