Cloud Architect
- London, United Kingdom
نُشرت أول أمس
عن الوظيفة
Cloud Architect (DevSecOps & LLMOps Engineer)
Location: London, United Kingdom (Hybrid – 50% work from client office)
Employment Type: Full-time
Security Clearance: Must hold or be eligible to obtain UK Security Check (SC) Clearance
About the Role
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.
In this role, you will:
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.
What You Need to Have to Be Considered
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:
Location: London, United Kingdom (Hybrid – 50% work from client office)
Employment Type: Full-time
Security Clearance: Must hold or be eligible to obtain UK Security Check (SC) Clearance
About the Role
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.
In this role, you will:
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.
What You Need to Have to Be Considered
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
- Candidates must be available to start within 4 weeks of receiving an offer.