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# AI Engineer (Fluent Portuguese & English)

- **Company:** Chubb
- **Location:** London, UK
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Nvidia CUDA, Continuous Integration, Python (Programming Language), Linux System Administration, Machine Learning, Modular Design, Performance Tuning, Search Technologies, WebSocket, Graphics Processing Unit (GPU), Retrieval-Augmented Generation, Large Language Models, Caching, Containerization, Kubernetes, Low Latency, Machine Learning Operations, Docker
- **Published:** August 19, 2026
- **Apply:** https://www.apply4u.co.uk/jobs/x/44530141/

## About the Role

quantization, caching strategies, and efficient batching.Production Engineering: Build and maintain real-time AI pipelines using WebSockets and SSE, ensuring seamless low-latency delivery for voice (ASR/TTS) and text applications.Architecture & MLOps: Deploy and orchestrate models within containerized microservice architectures (Docker/Kubernetes), ensuring robust monitoring, security, and scalability.Collaborative Delivery: Work closely with Business Analysts and internal stakeholders to bridge the gap between commercial requirements and technical implementation.Technical RequirementsProfessional Experience: 5+ years in AI/ML engineering with a documented history of moving complex models from research into production.Python Mastery: Deep proficiency in Python. You have a strong commitment to clean coding standards (SOLID/DRY), modular design, and comprehensive unit/integration testing.Generative AI Deep Dive: Hands-on experience with LLM training cycles, parameter-efficient fine-tuning
(PEFT), and sophisticated prompt engineering.Inference Stack: Experience with high-performance inference servers (e.g., vLLM, TGI, or Triton) and an understanding of how to optimize models for GPU deployment.Infrastructure: Comfortable working in Linux-based environments and proficient in managing containerized workloads and automated CI/CD pipelines.Advanced RAG: Experience building production-ready Retrieval-Augmented Generation systems, including vector database management and semantic search optimization.Preferred QualificationsExperience in the insurance or financial services sector.Deep knowledge of GPU architecture, CUDA, and hardware-level performance optimization.Familiarity with Document Intelligence frameworks (OCR, layout analysis, and multimodal extraction).MUST be fluent in Portuguese and EnglishWe offer in return!Competitive salary & pension scheme, discretionary bonus scheme, 25 days annual leave plus ability to purchase 5 additional days, hybrid working options, Private
Medical cover, Employee Share Purchase Plan, Life Assurance, Subsidised gym membership, Comprehensive Learning & development offerings, Employee Assistance program.Integrity. client focus. respect. excellence. teamworkOur core values dictate how we live and work. We're an ethical and honest company that's wholly committed to its clients. A business that's engaged in mutual trust and respect for its employees and partners. A place where colleagues perform at the highest levels. And a working environment that's collaborative and supportive.Diversity & Inclusion. At Chubb, we consider our people our chief competitive advantage and as such we treat colleagues, candidates, clients, and business partners with equality, fairness and respect, regardless of their age, disability, race, religion or belief, gender, sexual orientation, marital status or family circumstances.We are committed to ensuring our recruitment process is inclusive and accessible to all. If you have a
disability or long-term condition (for example dyslexia, anxiety, autism, a mobility condition or hearing loss) and need us to make any reasonable adjustments, changes or do anything differently during the recruitment process, please let us know.Full timePosting Date: 2026-04-28

## Description

AI Engineer (Fluent in Portuguese & English)Position OverviewWe are seeking an AI Engineer to join our Global Analytics team in London. This role is focused on the end-to-end lifecycle of production-grade AI, from training and fine-tuning specialized models to architecting high-performance inference pipelines.The ideal candidate views AI as a rigorous engineering discipline. Beyond building models, you will be responsible for writing high-quality, maintainable Python code and ensuring that every solution-whether a voice agent or a document processor-is built for reliability, low latency, and global scale.Key ResponsibilitiesModel Training & Fine-Tuning: Lead the adaptation of Large Language Models (LLMs) for domain-specific tasks using techniques like LoRA, QLoRA, and PEFT to balance performance with resource efficiency.Inference Optimization: Architect and optimize inference pipelines to minimize TTFT (Time to First Token) and maximize throughput. This includes implementing


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