AI Engineer (AWS, Gen AI)
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: Employee / Contractor B2B Target start date: ASAP Working hours: Full-time Compensation: €45,000 - €70,000 gross per year What You'll Architect As an AI Engineer in an AWS environment, you will help organisations transform complexity into measurable outcomes by combining technology, data, intelligence, and human decision-making. This role is both technical and consultative, perfect for someone who can combine hands-on development, cloud engineering, solution design, and client delivery. We're looking for professionals who can move AI initiatives from experimentation to enterprise-scale production environments. Key Responsibilities Design and develop Generative AI applications using Amazon Bedrock . Build Retrieval-Augmented Generation (RAG) solutions using Bedrock Knowledge Bases and enterprise data sources. Develop AI applications and services using Python and Boto3 . Design and optimise RAG pipelines, including chunking strategies, retrieval optimisation, metadata filtering, and context management. Implement semantic search solutions using Amazon OpenSearch . Design and build agent-based architectures using Bedrock Agents and AgentCore capabilities. Develop prompt engineering frameworks and reusable prompting strategies. Implement LLM evaluation methodologies , including LLM-as-a-Judge and automated evaluation frameworks. Design model routing and inference optimisation strategies. Apply GenAI observability, monitoring, and operational best practices . Contribute to AI governance, evaluation, and responsible AI initiatives. Support the industrialisation of AI solutions from PoC to production. Collaborate closely with Cloud Engineers, Data Engineers, Architects, and client stakeholders. Contribute to AI engineering best practices, standards, and reusable frameworks. 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, Artificial Intelligence, Data Engineering, or equivalent professional experience xperience as an AI Engineer , GenAI Engineer , Machine Learning Engineer, or similar role. Proven experience delivering Generative AI solutions in production environments. Experience implementing RAG architectures and LLM-powered applications. Strong Python development experience. Hands-on experience with Amazon Bedrock and modern GenAI tooling. Strong understanding of software engineering principles and API development. Experience collaborating within multidisciplinary teams. Professional proficiency in English. Technical & Professional Skills Expertise in Amazon Bedrock , including Foundation Models, Knowledge Bases, Bedrock Agents, and AgentCore capabilities . Experience designing, implementing, and optimising Retrieval-Augmented Generation (RAG) architectures and enterprise knowledge retrieval solutions. Strong Python and Boto3 development skills for building, integrating, and deploying AI-powered services. Experience implementing semantic search , Amazon OpenSearch , vector-based retrieval, metadata filtering, and search optimisation techniques. 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. Knowledge of LLM evaluation frameworks , including LLM-as-a-Judge, observability, monitoring, testing, and responsible AI practices. Understanding of LLM FinOps, model routing strategies, inference optimisation, and cost-performance trade-offs. Experience building APIs, integrating enterprise applications, and developing production-grade software solutions using modern engineering practices. Nice to Have Professional proficiency in French . Previous experience delivering RAG solution to production within an enterprise environment. Experience with vector databases , advanced retrieval techniques, and knowledge graph integrations. Knowledge of AI governance , responsible AI frameworks, model monitoring, and compliance requirements. Experience integrating GenAI solutions with Snowflake and enterprise data platforms. Exposure to MLOps , AI deployment pipelines, and CI/CD practices for machine learning and GenAI solutions. Experience designing multi-agent systems and complex AI orchestration workflows. Docker , containerisation, and experience deploying distributed cloud solutions AWS Certifications related to AI, Machine Learning, or Cloud Architecture. 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. ️ Any use of AI assistance during the interview process may result in immediate disqualification from the recruitment process. Equal Opportunity Statement We are committed to building an inclusive workplace and encourage applications from all backgrounds, regardless of race, ethnicity, gender identity, sexual orientation, age, disability, or any other protected characteristic.
Наблюдалась 2026-09-15, впервые 2026-09-01, источник — Indeed.