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We’re looking for a hands-on AI Engineer who’s passionate about turning AI into real business impact. In this role, you’ll build and ship production-ready AI systems, work comfortably in fast-changing environments, and focus on solutions that deliver measurable value. You understand that successful AI is as much about organisations and expectations as it is about technology.
Interested in shaping the future of AI with us?
We’d love to hear from you — apply now!
MSQ DX is the world's first digital impact company, formed through the integration of three leading digital agencies (26 DX, MMT Digital, and UDG). With over 500 experts across the UK, Germany, Spain, and the USA, we work with complex organisations including Porsche, Bosch, Vodafone, BCG, Vaillant, and Caesars Entertainment to translate digital experience into measurable business impact.
Learn more on our new website at www.msqdx.com
We'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 Responsibilities
AI 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 applications
- You 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 commercial viability
- You 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 opportunities
- Design AI-enabled future states working with your Deployment Strategist and client stakeholders to reimagine processes with AI capabilities
- Assess AI feasibility evaluating which problems are well-suited for AI, which approaches to use, and what ROI to expect
- Define success metrics working with your strategist partner to establish measurable outcomes that demonstrate business value
- Collaborate on use case prioritisation helping identify which AI opportunities deliver the highest impact relative to implementation complexity
Technical Pre-Sales & Demonstration (10%)
- Build rapid AI prototypes creating working demonstrations of AI capabilities in prospect-specific contexts within days
- Demonstrate AI possibilities showing prospective clients what AI can do for their specific business challenges with concrete examples
- Provide technical credibility establishing trust with client technical and business leaders through demonstrated AI expertise
- Assess client AI readiness evaluating data quality, technical infrastructure, and organisational capability to support AI initiatives
- Strong 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 scalability
- Strong business outcome focus, rapid iteration mindset, pragmatic problem-solving, and clear communication with non-technical stakeholders
- Comfortable with change management, close collaboration with a Deployment Strategist, and selecting the right AI approach for the business problem
- Speed-oriented and autonomous execution, learning agility in a fast-evolving AI landscape, travel flexibility, entrepreneurial mindset, and ethical AI awareness (safety, bias, privacy)
Essential Requirements
- University 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 deployed
- Fluent English (written and spoken) - additional languages (German, Spanish) are valuable for DACH and Spain regions
- Legal right to work in the region of employment (UK and EU)
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