AWS Engineer – AI/ML

Job not on LinkedIn

🔥 2 minutes ago

🇬🇧 United Kingdom – Remote

💵 £75k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

☁️ Cloud Engineer

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This company has sponsored UK Skilled Worker visas in the past.

👻 Ghost score 2%

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Cloud Bridge

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2018

💼 Consulting

🎯 Recruiter

🤝 B2B

Consulting • Recruitment • B2B

Cloud Bridge is a tech recruitment agency specializing in AWS and cloud/IT roles. The company connects cloud engineers, architects, and IT professionals with global clients and also recruits for its own internal team, focusing on remote and international placements. As part of Cloud Bridge and aligned with AWS (an AWS Premier Partner), it emphasizes deep cloud expertise to match technical talent with organizations using AWS.

📋 Description

• Build and deploy AI agents using Amazon Bedrock Agents, Strands framework, Knowledge Bases and Guardrails • Develop and operate ML training pipelines on Amazon SageMaker • Implement production infrastructure as Terraform IaC, including Lambda, EventBridge, DynamoDB, S3, SageMaker Pipelines, CloudWatch dashboards and observability • Build evaluation harnesses and CI-runnable test suites for AI/ML systems • Implement MLOps pipelines, including model registry, deployment automation, drift monitoring, active learning loops and retraining triggers • Deliver AWS Landing Zone and multi-account environments using Control Tower, Organizations and Terraform • Contribute to migration and modernisation engagements, including server migrations, database migrations, networking and application platform builds • Design and build data engineering pipelines for ML training data • Implement security hardening for AI and infrastructure workloads • Produce technical documentation, architecture diagrams, runbooks, operational handover material and findings reports • Participate in weekly project cadences with Solutions Architects, Project Managers and customer stakeholders • Deliver customer projects across GenAI, machine learning and broader AWS infrastructure within structured SOW-driven teams

🎯 Requirements

• 3+ years hands-on experience building solutions on AWS, including AI/ML workloads (Amazon Bedrock, SageMaker, or equivalent cloud ML platforms) • Strong Python engineering skills for production-grade ML pipelines, data processing, API integrations and evaluation frameworks • Experience with large language models and agentic AI patterns, including prompt engineering, RAG, tool use and agent frameworks • Solid understanding of EC2, VPC, Lambda, EventBridge, DynamoDB, S3, IAM, CloudWatch and RDS • Infrastructure as Code using Terraform (preferred) or CloudFormation/CDK • Experience building CI/CD pipelines and automated testing • Ability to work within structured delivery teams and deliver to SOW-defined scope and timelines • Experience with AWS agent frameworks and tooling such as Strands SDK, Amazon Bedrock AgentCore and Amazon Quick • Practical experience with Amazon SageMaker, including training jobs, inference endpoints, Pipelines and model registry • Experience delivering AWS migration programmes • Experience with AWS Landing Zones, Control Tower and multi-account governance • Familiarity with ML evaluation methodology, including confusion matrices, confidence calibration, ECE and F1 disaggregation • Knowledge of security review and threat modelling for AI systems • AWS certifications such as ML Specialty or Solutions Architect Associate, or equivalent • Experience delivering within a consultancy or Professional Services environment