AI Engineer (AWS)

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• Exclusive Resume Review Receive expert feedback with personalized suggestions to enhance your resume., * Design, develop and deploy Generative AI solutions using AWS AI services and modern LLM frameworks

• Build and optimise RAG (Retrieval Augmented Generation) pipelines, including chunking strategies, hybrid retrieval approaches and metadata filtering
• Develop AI applications using Python and AWS SDK (Boto3) to integrate with cloud-native services
• Implement and manage Amazon OpenSearch for semantic search and knowledge retrieval use cases
• Create and maintain Amazon Bedrock Knowledge Bases for enterprise AI solutions
• Design and evaluate Agentic AI architectures, including AI agents, orchestration frameworks and autonomous workflows
• Apply prompt engineering best practices and implement LLM-as-a-Judge evaluation frameworks to measure model quality and performance
• Contribute to LLM FinOps, including model routing strategies, inference optimisation and cost management
• Collaborate with data, cloud and business teams to deliver scalable AI solutions aligned with client objectives
• Provide technical guidance on AI architecture, testing methodologies and production deployment strategies, At Keyrus, salary ranges reflect different levels of mastery and impact within the same role - not different job titles.

• Bottom of the range You meet the core requirements and will need ramp-up time and support.

• Middle of the range You are fully autonomous from Day 1 and deliver consistently.

• Top of the range You are a reference for the role, mentor others, and raise the bar for the team.

Final offers are based on experience, autonomy, scope, and market context, and are discussed transparently during the process.

Responsible AI & Recruitment

At Keyrus, all stages of our recruitment process are conducted and evaluated by human recruiters and interviewers. To support accuracy and efficiency, AI may occasionally be used internally by our team exclusively for note-taking purposes during interviews. AI is never used to make decisions.

To ensure fairness, authenticity, and the protection of confidential and proprietary information, the use of AI tools by candidates during the recruitment process is strictly prohibited.

Our commitment to responsible AI practices ensures that hiring decisions are based solely on each candidate’s own skills, experience, judgment, and expertise.

Any use of AI assistance during the interview process may result in immediate disqualification from the recruitment process.

• You are curious, analytical, and motivated by solving meaningful business challenges.
• You enjoy turning complexity into clarity and action.
• You balance technical thinking with business understanding.
• You are comfortable working in collaborative and international environments.
• You take ownership of your work and follow through on commitments.
• You value continuous learning and are motivated by long-term professional growth.
• You communicate clearly and effectively with a variety of stakeholders., * Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Software Engineering, Data Science or a related field, or equivalent professional experience
• 5+ years of experience in Software Engineering, Data Engineering, Machine Learning Engineering or AI-related roles
• At least 2 years of hands-on experience developing and deploying Generative AI and RAG solutions
• Proven experience delivering RAG architecture into production
• Experience designing, implementing and supporting cloud-based applications in AWS
• Experience working in agile and multidisciplinary technical teams
• Professional proficiency in English

Technical & Professional Skills

• Strong proficiency in Python
• Hands-on experience with AWS SDK (Boto3)
• Experience building and optimising RAG architectures
• Knowledge of Amazon OpenSearch and enterprise search solutions
• Experience with Amazon Bedrock and Knowledge Bases
• Understanding of Agentic AI architectures and AI agent orchestration patterns
• Strong expertise in Prompt Engineering
• Experience implementing LLM evaluation frameworks, including LLM-as-a-Judge
• Knowledge of LLM FinOps, model routing and inference optimisation strategies
• Strong analytical, problem-solving and solution-design capabilities
• Ability to translate business requirements into scalable technical solutions

Nice to Have

• Professional proficiency in French
• Experience with LangGraph, LangChain, AWS Strands Agents or similar orchestration frameworks
• Experience in consulting or client-facing environments
• Knowledge of MLOps, CI/CD and AI deployment best practices
• AWS certifications, particularly in AI, Machine Learning or Cloud Architecture
• Exposure to international projects and multicultural teams
• Experience evaluating and benchmarking LLM-based applications in production environments

What Makes You Successful

• You focus on outcomes rather than activity.
• You approach challenges with curiosity and pragmatism.
• You communicate complex concepts in a clear and accessible way.
• You are comfortable navigating ambiguity and finding practical solutions.
• You contribute to collective intelligence by sharing knowledge and supporting others.
• You combine autonomy with collaboration.
• You continuously look for opportunities to improve systems, processes, and results.

Premium Full-time Enterprise Search Knowledge Base Machine Learning Architects Bridge 70.000 EUR, * Competitive salary aligned with your experience and the data market

• Meal allowance: €10.20/day
• Flexible benefits plan
• Private medical insurance
• 22 days of annual leave, increasing every 3 years (up to 25 days)
• Continuous learning via KLX - Keyrus Learning Experience
• A collaborative, international, and human-centred work environment

Keyrus is an international group of 2,800 consultants and experts across 28 countries, built on a single conviction: AI does not transform businesses. Architected intelligence does.

For more than 30 years, we have been building the data foundations that make intelligent systems work - designing the Operating System of the intelligent enterprise, where intelligence is embedded into the core of business processes to create sustainable value: we operationalise intelligence.

AI does not replace humans. It repositions us to a place no system can follow: understanding, deciding, designing, and creating.

At Keyrus, you will not just develop skills - you will develop judgment. Your expertise sharpens with every system you architect, every client challenge you solve, and every deployment that compounds on the last.

Over time, you grow into one of the rarest professionals of the intelligence era: someone who bridges data, AI, and human decision-making at scale, across industries and geographies. This is not a role you fill. It is a discipline you master and a story you help write to become a Keyrus Architect of Intelligence.

Technology amplifies. Keyrus culture differentiates. Industrial discipline connects the two.