Senior AI Engineer

<p data-start="101" data-end="238"><strong data-start="101" data-end="144">Senior AI Engineer</strong><br data-start="144" data-end="147">Location: London (Hybrid) | <strong data-start="175" data-end="192">Practice Area</strong>: Technology & Engineering | Type: Permanent</p> <p data-start="240" data-end="346"><strong data-start="240" data-end="346">Empower the next frontier of AI with Capco. Shape, build, and deliver future-ready generative systems.</strong></p> <p><strong>The Role</strong></p> <p>We’re looking for a Senior AI Engineer (Senior/Principal Consultant) to join our Technology Delivery team. In this role, you’ll combine deep expertise in AI/ML engineering and software development to design, build, and deploy advanced generative AI and agentic systems for leading financial services clients. You’ll work hands-on across the full AI engineering lifecycle, from architecting intelligent multi-agent systems to deploying scalable production-grade AI applications within enterprise environments. As a senior consultant, you’ll also collaborate closely with multidisciplinary teams and client stakeholders to drive innovation, accelerate adoption, and deliver measurable business impact.</p> <p><strong>What You’ll Do</strong></p> <ul> <li>Architect and develop autonomous AI systems leveraging multi-modal large language models across text, image, audio, and video</li> <li>Design and implement agentic workflows using prompt engineering, Retrieval-Augmented Generation (RAG), APIs, and enterprise data integrations</li> <li>Fine-tune, optimize, and deploy large language and multi-modal models with a focus on scalability, reliability, and low-latency performance</li> <li>Build scalable MLOps pipelines and cloud-native AI applications to support secure, production-grade deployments</li> <li>Collaborate with clients and cross-functional teams to shape AI engineering strategy and accelerate GenAI adoption across complex environments</li> </ul> <p><strong>What We’re Looking For</strong></p> <ul> <li>Bachelor’s degree or higher in Computer Science, Artificial Intelligence, Engineering, or a related STEM discipline</li> <li>Proven hands-on experience deploying LLMs and multi-modal AI models within enterprise or large-scale production environments</li> <li>Strong software engineering expertise in Python, including backend development, API design, and distributed systems</li> <li>Solid understanding of scalable MLOps, observability, CI/CD practices, and cloud-native AI deployment architectures</li> <li>Excellent communication, stakeholder management, and problem-solving skills within agile delivery environments</li> </ul> <p><strong>Bonus Points For</strong></p> <ul> <li>Experience building AI agent frameworks or autonomous orchestration platforms</li> <li>Knowledge of vector databases, semantic search, and advanced RAG architectures</li> <li>Experience with cloud platforms such as AWS, Azure, or