Forward Deployed AI Engineer
$70,000–$85,000 year
HybridAlcobendas, Madrid, Spain
Job Summary
Co-create solutions with business and technical stakeholders through workshops, rapid iterations, and hands-on delivery. 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.
Required Qualifications
- 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
- 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
Desired Qualifications
- 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
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