Senior AWS AI Engineer

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 are looking for professionals who think like architects and act like builders, designing scalable AI solutions that successfully move from proof of concept into production environments.

Key Responsibilities

• Design and implement serverless and cloud-native architectures on AWS.

• Build and deploy Generative AI applications using Amazon Bedrock, foundation models, Knowledge Bases, Agent capabilities, guardrails, and related AWS services.

• Develop AI applications and services using Python and Boto3, leveraging AWS-native capabilities and APIs.

• Design and implement production-grade Retrieval-Augmented Generation (RAG) solutions using Amazon OpenSearch, Bedrock Knowledge Bases, vector search technologies, and LLMs.

• 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 into scalable production environments.

• 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, 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

• Expertise in Amazon Bedrock, including Foundation Models, Knowledge Bases, Bedrock Agents, and AgentCore capabilities.

• Experience designing, implementing, and optimising RAG architectures, retrieval pipelines, and AI-powered applications.

• 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.

• AWS certifications such as AWS Certified Solutions Architect, AWS Certified Developer, or AI-specialised certifications.

• Experience with Terraform and Infrastructure as Code.

• 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.

⚠️ 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.