Cloud Architect

As a Cloud Architect (DevSecOps & LLMOps Engineer) , you will make an impact by designing, building, securing, and operating scalable cloud infrastructure and enterprise Generative AI applications that drive automation, observability, and modern LLMOps practices. You will be a valued member of our Cloud & AI Engineering team and work collaboratively with architects, developers, security teams, and business stakeholders to deliver secure, resilient, scalable, and cost-effective cloud and AI solutions using AWS Bedrock and related technologies., * Design, implement, and support secure, scalable AWS infrastructure and AI platforms using Terraform, GitHub Actions, Ansible, ECS/Fargate, and AWS native services.

• Build and operationalise enterprise GenAI solutions using Amazon Bedrock, LLMs, RAG pipelines, vector databases, embeddings, chunking strategies, workflow orchestration (DAG/agentic), and AI observability.
• Develop and maintain CI/CD pipelines, Infrastructure as Code, API integrations, cloud security, IAM governance, monitoring, logging, and production BAU support.
• Configure and manage application observability using Datadog (or equivalent), including dashboards, APM, log analytics, infrastructure monitoring, alerting, and operational health reporting.
• Collaborate with architects, developers, security teams, and business stakeholders to deliver secure, resilient, scalable, and cost-effective cloud and AI solutions.

• Strong hands-on experience with AWS services including Amazon Bedrock, ECS/Fargate, Lambda, EC2, API Gateway, VPC, ALB, IAM, CloudWatch, S3, EFS, DynamoDB, and Neptune, alongside Infrastructure as Code using Terraform.
• Strong experience with DevSecOps practices including GitHub Actions, Ansible, Docker, CI/CD automation, security scanning, secrets management, monitoring, logging, and production support.
• Good understanding of LLMOps concepts including LLMs, RAG, embeddings, chunking, vectorisation, vector databases, semantic search, prompt engineering, workflow orchestration (DAG/LangGraph), AI guardrails, and model evaluation.
• Strong experience with API Management platforms such as Amazon API Gateway, Kong, Apigee, or equivalent - with the ability to design, configure, and implement API proxy workflows, authentication, routing, policies, transformations, and API integrations.
• Strong experience with Datadog (or equivalent monitoring platform) for dashboard creation, application monitoring, alert configuration, APM, log analytics, and performance troubleshooting.
• Excellent communication, stakeholder management, and client-facing skills.
• Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.
• Must currently reside in the United Kingdom.
• Must be available to start within 4 weeks of receiving an offer.
• Must hold or be eligible to obtain UK Security Check (SC) Clearance.

These Will Help You Stand Out

• Experience with Kubernetes/EKS, Docker, ServiceNow, Jira, GitHub Runners, CloudFormation, Route 53, WAF, EventBridge, Step Functions, and serverless architectures.
• Hands-on experience with Python development for automation, API integrations, scripting, and cloud-native application development.
• Experience building AI data pipelines, including document ingestion, preprocessing, metadata enrichment, chunking, embedding generation, vector indexing, and retrieval workflows.
• Familiarity with AI prompt development, prompt tuning, prompt templates, and prompt evaluation techniques.
• Exposure to vector databases, OpenSearch, LangChain/LangGraph, knowledge graphs (Neptune), cloud networking, security best practices, cost optimisation, and enterprise production support.

Additional eligibility requirements:

· Candidates must hold or be eligible to obtain UK Security Check (SC) Clearance