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.
Job location: Portugal (Hybrid model - flexible)
Contract type: Employee contract
Target start date: September 2026
Working hours: Full-time (40h/week)
Compensation: €65k–€78k per year
As a Forward Deployed AI Engineer, you work at the heart of a client's most pressing AI challenges, turning intent into an operational, measurable result in weeks rather than months. This is an experienced individual-contributor role for someone who combines hands-on engineering, architectural judgment, and business understanding.
You own the problem from ambiguity through to execution - understanding the real context, building and deploying the solution, and proving, not declaring, that it creates value. Once the terrain is understood, you become the reference the team relies on to make that result last.
Your responsibilities
Co-create solutions with business and technical stakeholders through workshops, rapid iterations, and hands-on delivery.
Locate, qualify, and secure access to the data required for each use case, working directly with Data Engineers
Translate use cases into production-ready GenAI and agentic AI solutions, including RAG architectures, intelligent assistants, and AI-enabled workflows.
Prototype, test, deploy, monitor, and improve solutions in real client environments using feedback from users and domain experts.
Work with Data Engineers, Software Engineers, Foundations Architects, Governance experts, Business Value Advisors, and Service Delivery Managers to deliver sustainable outcomes.
Balance speed, quality, cost, security, and maintainability while making clear technical and delivery trade-offs.
Define success criteria from the outset, including adoption, performance, reliability, risk, cost, and measurable business value.
Ensure solutions are documented, governed, and transferable so clients can operate them with confidence.
Turn successful delivery into reusable patterns, accelerators, and building blocks that strengthen future engagements.
You are a hands-on engineer who thinks like an architect and acts like a builder. You are comfortable working closely with the client, the problem, and the delivery, and you make sound decisions in complex, evolving environments.
You enjoy solving operational challenges, not only exploring technical concepts.
You communicate clearly with both technical teams and senior business stakeholders.
You navigate ambiguity with confidence, validate assumptions, and adapt quickly.
You take ownership of outcomes and raise risks or changing priorities early.
You understand that AI value depends on the full system: data, workflows, governance, adoption, and measurement.
You naturally look for what can be reused, improved, and scaled.
5–10 years of relevant experience in AI Engineering, Machine Learning, Software Engineering, Data Engineering, or technical consulting.
Hands-on experience delivering AI, GenAI, or software solutions into production.
Experience working directly with clients or in complex stakeholder environments.
Evidence of turning complex use cases into adopted, measurable solutions.
A degree in Computer Science, Engineering, Artificial Intelligence, Data Science, or a related field, or equivalent practical experience.
Ability to work effectively in multidisciplinary environments.
Professional proficiency in English.
Strong Python development skills, API integration experience, and modern software-engineering practices.
Hands-on experience with Large Language Models (LLMs), GenAI architectures, prompt workflows, and model/provider selection.
Experience with RAG, embeddings, vector search, AI agents, and agentic workflows.
Familiarity with frameworks such as LangChain, LlamaIndex, LangGraph, Semantic Kernel, AutoGen, or comparable tools.
Experience integrating AI into enterprise systems, APIs, and business workflows.
Experience with at least one major cloud platform: Azure, AWS, or GCP.
Working knowledge of Docker, Git, CI/CD, production deployment, monitoring, and evaluation.
Understanding of MLOps / LLMOps, security, data privacy, governance, and Responsible AI principles.
Experience in consulting or client-facing environments.
Experience with multimodal models, fine-tuning, model adaptation, or open-source LLMs.
Front-end or full-stack development experience, for example, Node.js or React.
Consulting or professional-services experience.
Exposure to regulated industries or enterprise governance requirements.
You combine technical credibility, pragmatism, and end-to-end ownership.
You focus on real-world outcomes, adoption, and measurable value—not only the solution itself.
You move quickly while balancing speed, quality, cost, and risk.
You build trust and become a reliable partner in complex client environments.
You operate effectively under pressure in client environments, where progress and results are continuously visible.
You know when to go deep technically and when to orchestrate the right expertise.
You continuously improve, reuse, and scale what works across engagements.
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
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.
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.
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.
