Descripción de la oferta
Role Overview Forward Deployed AI Engineer – a forward‑deployed, hands‑on engineering role delivering AI solutions within weeks. The role combines architecture, engineering and business‑understanding to own the problem from ambiguity to execution. Location & Contract Madrid, Spain (Hybrid – flexible) Employee / contract Full‑time (40 hours/week) Target start date: September 2026 Compensation: €70k–€85k per year 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 Gen AI 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. Who You Are Hands‑on engineer who thinks like an architect and acts like a builder. Communicates clearly with both technical teams and senior business stakeholders. Solves operational challenges, not only exploring technical concepts. Navigates ambiguity with confidence, validates assumptions, and adapts quickly. Takes ownership of outcomes and raises risks or changing priorities early. Understands that AI value depends on the full system: data, workflows, governance, adoption, and measurement. Seeks reusable, improvable, and scalable solutions. Qualifications & Experience 5–10 years of relevant experience in AI Engineering, Machine Learning, Software Engineering, Data Engineering, or technical consulting. Hands‑on experience delivering AI, Gen AI, 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. Technical & Professional Skills Strong Python development skills, API integration experience, and modern software‑engineering practices. Hands‑on experience with Large Language Models (LLMs), Gen AI architectures, prompt workflows, and model/provider selection. Experience with RAG, embeddings, vector search, AI agents, and agentic workflows. Familiarity with frameworks such as Lang Chain, Llama Index, Lang Graph, Semantic Kernel, Auto Gen, 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. Nice to Have 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. Success Criteria Combines technical credibility, pragmatism, and end‑to‑end ownership. Focuses on real‑world outcomes, adoption, and measurable value—not only the solution itself. Moves quickly while balancing speed, quality, cost, and risk. Builds trust and becomes a reliable partner in complex client environments. Operates effectively under pressure where progress and results are continuously visible. Knows when to dive deep technically and when to orchestrate the right expertise. Continuously improves, reuses, and scales what works across engagements. What We Offer Competitive salary, paid in 14 instalments (or 12 from day one). Annual performance bonus. Meal allowance (Restaurant Tickets): €1,800/year net, distributed over 11 monthly reloads. Flexible retribution plan: transport & daycare tickets. Private medical insurance with Sanitas (no copays, dental included). 22 days of annual leave, increasing every 3 years (up to 26 days). 14 public holidays (Madrid calendar). December 24th and 31st considered company holidays when they fall on working days. Continuous learning via KLX – Keyrus Learning Experience. A collaborative, international, and human‑centred work environment. Salary Ranges Salary ranges reflect different levels of mastery and impact within the same role. 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. Recruitment & Responsible AI All stages of the recruitment process are conducted by human recruiters and interviewers. AI may be used internally for note‑taking during interviews, but is never used to make decisions. Candidates are strictly prohibited from using AI tools during 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. #J-18808-Ljbffr
