Deployed AI Engineer (all genders)Full TimeBarcelona
Role details
Job location
Tech stack
Job description
commercial viabilityYou work embedded within client organisations to understand real processes, drive adoption, and enable AI-led change Business Process Transformation (15%)Map current business processes understanding how work gets done today, identifying bottlenecks, and spotting automation opportunitiesDesign AI-enabled future states working with your Deployment Strategist and client stakeholders to reimagine processes with AI capabilitiesAssess AI feasibility evaluating which problems are well-suited for AI, which approaches to use, and what ROI to expectDefine success metrics working with your strategist partner to establish measurable outcomes that demonstrate business valueCollaborate on use case prioritisation helping identify which AI opportunities deliver the highest impact relative to implementation complexityTechnical Pre-Sales & Demonstration (10%)Build rapid AI prototypes creating working demonstrations of AI capabilities in prospect-specific contexts within daysDemonstrate
Requirements
AI possibilities showing prospective clients what AI can do for their specific business challenges with concrete examplesProvide technical credibility establishing trust with client technical and business leaders through demonstrated AI expertiseAssess client AI readiness evaluating data quality, technical infrastructure, and organisational capability to support AI initiativesStrong AI/ML implementation experience (2+ years) building and deploying production AI systems, with hands-on expertise in LLMs and generative AI (GPT-4, Claude, Llama), including prompt engineering, RAG, fine-tuning, and AI agent development (LangChain, AutoGen, CrewAI or similar)Strong Python skills, solid data engineering capabilities (pipelines, vector databases, ETL), API and integration experience, and practical ML foundations (scikit-learn, PyTorch, TensorFlow)Proven experience shipping AI systems to production, with cloud infrastructure knowledge (AWS, Azure, GCP incl. GPU/serverless), full-stack development around AI applications, DevOps/MLOps practices (CI/CD, monitoring, model versioning), and performance optimisation across cost, latency, and scalabilityStrong business outcome focus, rapid iteration mindset, pragmatic problem-solving, and clear communication with non-technical stakeholdersComfortable with change management, close collaboration with a Deployment Strategist, and selecting the right AI approach for the business problemSpeed-oriented and autonomous execution, learning agility in a fast-evolving AI landscape, travel flexibility, entrepreneurial mindset, and ethical AI awareness (safety, bias, privacy)Essential RequirementsUniversity degree in Computer Science, AI/ML, Data Science, or related technical field (or equivalent practical experience)Portfolio of production AI/ML systems you've built and deployedFluent English (written and spoken) - additional languages (German, Spanish) are valuable for DACH and Spain regionsLegal right to work in the region of employment (UK and EU)