Live opening · Posted 5 days ago

AI & Cloud Engineer (AWS)

Keyrus · Alforja, Catalonia, Spain (Remote)
Linkedin Yes
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At a glance

The key details from the original listing.

Posted 5 days ago
CompanyKeyrus
LocationAlforja, Catalonia, Spain (Remote)
Salary300 EUR/day - 400 EUR/day
Work modeYes
SourceLinkedin
Listed5 days ago

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About the role

Description supplied by the original job listing.

Why Keyrus, Why Now!
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.
Role Details
📍 Job location: Portugal or Spain (Remote model)
🕒 Contract type: Contractor B2B
🗓 Target start date: ASAP
⏰ Working hours: Full-time
💵 Compensation: €300 - €400 B2B daily rate
📋 What You'll Architect
As an AI & Cloud Engineer, you will help organisations transform complexity into measurable outcomes by combining technology, data, intelligence, and human decision-making, by designing and building cloud-native AI solutions on AWS. The role combines strong AWS engineering skills with hands-on experience in Generative AI, RAG architectures and LLM-based applications. This role is both technical and consultative, perfect for someone who can combine hands-on development, cloud engineering, solution design, and client delivery.
You will work on solutions that need to move beyond prototypes into secure, scalable and production-ready environments. We are looking for professionals who think like architects and act like builders.
Key Responsibilities
Design and implement serverless and cloud-native architectures on AWS.
Build and deploy Generative AI and RAG solutions using Amazon Bedrock and related AWS services.
Develop AI services and integrations using Python and Boto3.
Implement retrieval pipelines combining Amazon OpenSearch, Bedrock Knowledge Bases and LLMs.
Design agentic architectures, including AWS Strands Agents or equivalent frameworks.
Build and maintain cloud infrastructure using Terraform / Infrastructure as Code.
Deploy and operate workloads using services such as AWS Lambda, ECS/Fargate, Cognito, IAM and Step Functions.
Define and implement LLMOps practices, including model routing, evaluation, monitoring and dedicated inference profiles.
Apply prompt engineering and LLM evaluation techniques, including LLM-as-a-judge approaches.
Work closely with technical and business stakeholders to translate requirements into robust solutions.
👤 Who You Are
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
You enjoy building practical solutions and bringing AI use cases into real-world production environments.
🛠️ What You Bring
Qualifications & Experience
Relevant academic background in Computer Science, Software Engineering, Information Technology, or equivalent practical experience.
5+ years of experience in AWS Cloud Engineering, Software Engineering, or Cloud Solution Development.
2+ years of hands-on experience building and deploying Generative AI and LLM-based applications.
Proven experience designing and implementing cloud-native architectures on AWS.
Demonstrated experience implementing at least one production-grade RAG solution.
Experience working in agile delivery teams and multidisciplinary technical environments.
Professional proficiency in English.
Technical & Professional Skills
Solid experience with Amazon Bedrock, including foundation models, Knowledge Bases, AgentCore/runtime concepts and guardrails.
Strong Python development skills and experience with Boto3.Practical experience designing, implementing, and optimising RAG architecture, retrieval pipelines, and AI-powered applications.
Experience with Terraform and Infrastructure as Code.
Good understanding of Amazon OpenSearch and vector/retrieval architectures.
Knowledge of LLM evaluation frameworks and orchestration, including LLM-as-a-Judge, observability, monitoring, testing, and responsible AI practices.
Understanding of agentic architectures, multi-step reasoning workflows, and orchestration patterns for GenAI applications.
Experience with prompt engineering, prompt evaluation, and techniques for improving LLM response quality and reliability.
Ability to make architectural decisions, explain trade-offs and defend technical choices with both technical teams and clients.
Experience building APIs, integrating enterprise applications, and developing production-grade software solutions using modern engineering practices.
Nice to Have
Professional proficiency in French.
AWS certifications such as AWS Certified Solutions Architect, AWS Certified Developer, or AI-specialised certifications.
Experience deploying workloads on AWS Lambda, ECS/Fargate, Amazon RDS, Cognito, IAM, and Step Functions.
Understanding of AWS security, including cross-account IAM and enterprise governance practices.
Exposure to MLOps, AI deployment pipelines, and CI/CD practices for machine learning and GenAI solutions.
Exposure to Architecture Review Boards, cloud governance frameworks, or enterprise architecture practices.
Experience working in consulting or client-facing delivery environments.
Exposure to international projects or multicultural teams.
⭐ 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.
🎁 What We Offer at Keyrus Portugal
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
💰 How Our Salary Ranges Work
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.
⚠

Work arrangement
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