Generative AI Architect - Enterprise AI Systems,March 27, 2026### Job DescriptionLocation: London, UK Work Model: On-site Role Type: Full-TimeWe are looking for a Generative AI Architect with strong experience in designing and scaling AI systems to join our client’s on-site team in London.This role focuses on defining the architecture, infrastructure, and operational practices for enterprise-grade Generative AI solutions. You will bridge the gap between prototype and production, ensuring AI systems are scalable, reliable, observable, and continuously improving.—### What You’ll Do#### Infrastructure & Cloud* Design and manage cloud infrastructure for AI workloads using platforms such as Amazon Web Services, Google Cloud, or Microsoft Azure* Implement Infrastructure-as-Code and containerisation strategies using Docker and Kubernetes* Ensure scalability, security, and cost optimisation of AI deployments—#### AI Operations (MLOps / AIOps)*

Establish CI/CD pipelines for AI systems, including automated testing, deployment, and rollback* Define AI software development lifecycle (AI SDLC) practices, including workflows, code reviews, and release processes* Implement best practices for model deployment, versioning, and experiment tracking—#### Evaluation & Quality* Design evaluation pipelines for LLM outputs and RAG system performance* Implement automated testing strategies (regression testing, benchmark suites)* Define quality gates and acceptance criteria for AI releases* Apply evaluation methodologies including custom metrics and LLM-based evaluation approaches—#### Monitoring & Observability* Build observability frameworks for AI systems including logging, tracing, and alerting* Implement monitoring solutions using tools such as Weights & Biases or custom platforms* Define SLIs/SLOs for AI system performance and reliability* Establish incident response processes and operational best practices for AI platforms—### What We’re Looking For#### Required Skills & Experience* Strong experience with cloud platforms and Infrastructure-as-Code* Hands-on experience with containerisation and orchestration (Docker, Kubernetes)* Solid understanding of MLOps / AIOps practices (CI/CD for AI, model deployment, lifecycle management)* Experience with Generative AI technologies including LLMs, RAG architectures, and vector databases* Strong software architecture background, designing distributed and scalable systems* Experience with microservices and API-first architectures* Ability to design systems for non-deterministic, AI-driven applications* Strong programming skills (Python, TypeScript or similar)* Experience with monitoring, observability, and production systems* Excellent communication skills and ability to work on-site with cross-functional teams—#### Nice to Have* Experience with frameworks such as LangChain, LlamaIndex, or similar* Experience with model fine-tuning techniques (LoRA, QLoRA, PEFT)* Background in NLP (embeddings, semantic search, tokenisation)* Experience with open-source AI ecosystems such as Hugging Face* Familiarity with security and compliance requirements for AI systems* Experience in regulated industries (e.g. finance, healthcare)* Contributions to open-source AI/ML tools—Location: London, UK Work Model: On-site Role Type: Full-TimeLocation,Experience levelMid-Senior level## Work Location

AIOps)* Establish CI/CD pipelines for AI systems, including automated testing, deployment, and rollback* Define AI software development lifecycle (AI SDLC) practices, including workflows, code reviews, and release processes* Implement best practices for model deployment, versioning, and experiment tracking—#### **Evaluation & Quality* Design evaluation pipelines for LLM outputs and RAG system performance* Implement automated testing strategies (regression testing, benchmark suites)* Define quality gates and acceptance criteria for AI releases* Apply evaluation methodologies including custom metrics and LLM-based evaluation approaches—#### Monitoring & Observability* Build observability frameworks for AI systems including logging, tracing, and alerting* Implement monitoring solutions using tools such as Weights & Biases or custom platforms* Define SLIs/SLOs for AI system performance and reliability* Establish incident response processes and operational best practices for AI platforms—### What We’re Looking For#### Required Skills & Experience* Strong experience with cloud platforms and Infrastructure-as-Code* Hands-on experience with containerisation and orchestration (Docker, Kubernetes)* Solid understanding of MLOps / AIOps practices (CI/CD for AI, model deployment, lifecycle management)* Experience with Generative AI technologies including LLMs, RAG architectures, and vector databases* Strong software architecture background, designing distributed and scalable systems* Experience with microservices and API-first architectures* Ability to design systems for non-deterministic, AI-driven applications* Strong programming skills (Python, TypeScript or similar)* Experience with monitoring, observability, and production systems* Excellent communication skills and ability to work on-site with cross-functional teams—#### Nice to Have* Experience with frameworks such as LangChain, LlamaIndex, or similar* Experience with model fine-tuning techniques (LoRA, QLoRA, PEFT)* Background in NLP (embeddings, semantic search, tokenisation)* Experience with open-source AI ecosystems such as Hugging Face* Familiarity with security and compliance requirements for AI systems* Experience in regulated industries (e.g. finance, healthcare)* Contributions to open-source AI/ML tools—Location: London, UK Work Model: On-site Role Type: Full-TimeLocation,Experience levelMid-Senior level## Work Location #J-18808-Ljbffr