Generative AI Architect & Enterprise AI Systems

Talenzon group; Greater London; On-site; GBP 125,000 - 150,000; Full time

Job summary

A leading technology company is seeking a Generative AI Architect to design infrastructure and operational practices for scalable AI solutions in London. The ideal candidate has strong experience with cloud platforms, MLOps practices, and generative AI technologies. You will define, implement, and monitor AI systems to ensure they are reliable and continuously improving. Join an on-site team focused on bridging prototypes to production for enterprise-grade AI applications.

Qualifications

• Strong experience with Infrastructure-as-Code.
• Solid understanding of CI/CD for AI systems.
• Experience with monitoring and observability.

Responsibilities

• Design cloud infrastructure for AI workloads.
• Establish CI/CD pipelines for AI systems.
• Define quality gates for AI releases.
• Build observability frameworks for AI systems.

Skills

Experience with cloud platforms

Hands-on experience with Docker and Kubernetes

Understanding of MLOps / AIOps practices

Experience with Generative AI technologies

Strong programming skills in Python or TypeScript

Excellent communication skills

Tools

Amazon Web Services

Google Cloud

Microsoft Azure

Weights & Biases

Job description

# Generative AI Architect – Enterprise AI Systems,March 27, 2026### Job Description**Location:** 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