Deployed AI Engineer (all genders)Full TimeBarcelona

Ai-enabled
Barcelona, Spain
8 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English, Spanish, German
Experience level
Intermediate

Job location

Barcelona, Spain

Tech stack

API
Artificial Intelligence
Amazon Web Services (AWS)
Azure
Cloud Computing
Continuous Integration
Information Engineering
ETL
DevOps
Python
Performance Tuning
TensorFlow
Systems Integration
Google Cloud Platform
PyTorch
Large Language Models
Prompt Engineering
Scikit Learn
Information Technology
Machine Learning Operations
Virtual Agents
GPT
Software Version Control
Serverless Computing

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)

About the company

impact.Learn more on our new website at www.msqdx.comWe're at the forefront of helping enterprises move beyond AI experimentation into production deployment and business transformation. Our AI-enabled delivery approach combines deep technical expertise with business outcome focus, helping clients navigate the critical "trial-to-production" gap that's holding back enterprise AI adoption.Key ResponsibilitiesAI Implementation & Deployment (ca. 75%)You design, build, and deploy production-ready AI solutions that deliver measurable business impact - from intelligent automation and AI agents to predictive analytics and generative AI applicationsYou move fast, taking ideas from prototype to production, using modern frameworks (e.g. LangChain, AutoGen) and foundation models (OpenAI, Anthropic, open-source LLMs)You integrate AI into existing business systems via APIs and data pipelines, ensure safe and reliable operation through governance and monitoring, and optimise performance and costs for

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