Lead AI Engineer
Capco is hiring a Lead AI Engineer (Senior/Principal Consultant) in London (hybrid) to architect and deploy generative AI and agentic systems for financial services clients. Day to day involves building multi-modal LLM solutions, RAG/prompt-engineered agent workflows, Python backends/APIs, and scalable MLOps pipelines while guiding teams and clients.
- Compensation
- Not disclosed
- Location
- UK - London
- Work setup
- Not specified
- Seniority
- Lead
- Employment
- Full time
- Experience
- Not specified
- Category
- Ai engineering
- Posted
Skills
Must have
- Bachelor's degree or higher in Computer Science, AI, or related STEM fields
- Hands-on experience deploying LLMs and multi-modal models at scale
- Strong engineering background in Python with proven backend and API development skills
- Solid understanding of scalable MLOps, observability, and cloud-native AI deployment
- Excellent communication, problem-solving, and project management skills in agile environments
Nice to have
- Experience with agentic frameworks (e.g., LangChain, LlamaIndex)
- Experience in deep learning frameworks and front-end development
- Familiarity with Langfuse, Langsmith, or other LLM observability tools
- Understanding of Model Context Protocol and bias/hallucination mitigation techniques
- Previous success in integrating GenAI solutions into enterprise-scale systems
Full description
Lead AI Engineer (Senior/Principal Consultant)
Location: London (Hybrid) | Practice Area: Technology & Engineering | Type: Permanent
Empower the next frontier of AI with Capco. Shape, build, and deliver future-ready generative systems.The Role
We’re looking for a Lead AI Engineer (Senior/Principal Consultant) to join our Technology Delivery Team. You’ll combine your expertise in AI/ML engineering and software development to build and deploy cutting-edge generative AI and agentic systems across the financial services sector. As a hands-on leader, you’ll architect AI solutions, embed them within enterprise environments, and drive impactful outcomes through advanced engineering, scalable pipelines, and deep cross-functional collaboration.
What You’ll Do
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Architect and develop autonomous AI systems integrating multi-modal LLMs (text, image, audio, video)
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Design agentic workflows enabling AI agents to interact with data sources and APIs using prompt engineering and RAG
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Fine-tune, optimize, and deploy large language and multi-modal models with a focus on performance and latency
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Build scalable MLOps pipelines and full-stack applications to support robust, production-grade AI deployments
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Guide multidisciplinary teams and clients through strategic decisions in AI engineering and GenAI adoption
What We’re Looking For
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Bachelor’s degree or higher in Computer Science, AI, or related STEM fields
-
Hands-on experience deploying LLMs and multi-modal models at scale
-
Strong engineering background in Python with proven backend and API development skills
-
Solid understanding of scalable MLOps, observability, and cloud-native AI deployment
-
Excellent communication, problem-solving, and project management skills in agile environments
Bonus Points For
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Experience with agentic frameworks (e.g., LangChain, LlamaIndex)
-
Experience in deep learning frameworks and front-end development
-
Familiarity with Langfuse, Langsmith, or other LLM observability tools
-
Understanding of Model Context Protocol and bias/hallucination mitigation techniques
-
Previous success in integrating GenAI solutions into enterprise-scale systems