AWS Engineer – AI/ML

This is a fully remote position, open to applicants in United Kingdom.

📋 Description

• Develop and implement AI agents utilizing Amazon Bedrock Agents, the Strands framework, Knowledge Bases, and Guardrails.

• Create and manage machine learning training pipelines on Amazon SageMaker.

• Establish production infrastructure using Terraform Infrastructure as Code (IaC), encompassing Lambda, EventBridge, DynamoDB, S3, SageMaker Pipelines, CloudWatch dashboards, and observability tools.

• Construct evaluation harnesses and continuous integration test suites for AI/ML systems.

• Execute MLOps pipelines that include model registry, deployment automation, drift monitoring, active learning loops, and retraining triggers.

• Provide AWS Landing Zone and multi-account setups through Control Tower, Organizations, and Terraform.

• Assist in migration and modernization initiatives, including server migrations, database transitions, networking, and application platform developments.

• Design and implement data engineering pipelines for machine learning training datasets.

• Enforce security enhancements for AI and infrastructure workloads.

• Generate technical documentation, architecture diagrams, runbooks, operational handover materials, and findings reports.

• Engage in weekly project meetings with Solutions Architects, Project Managers, and customer stakeholders.

• Execute customer projects across GenAI, machine learning, and broader AWS infrastructure within organized SOW-driven teams.

⛳️ Requirements

• Minimum of 3 years of hands-on experience in developing solutions on AWS, particularly with AI/ML workloads (Amazon Bedrock, SageMaker, or similar cloud ML platforms).

• Proficient in Python engineering for production-grade ML pipelines, data processing, API integrations, and evaluation frameworks.

• Familiarity with large language models and agentic AI methodologies, including prompt engineering, RAG, tool usage, and agent frameworks.

• Strong understanding of AWS services such as EC2, VPC, Lambda, EventBridge, DynamoDB, S3, IAM, CloudWatch, and RDS.

• Experience with Infrastructure as Code using Terraform (preferred) or CloudFormation/CDK.

• Proven ability to build CI/CD pipelines and conduct automated testing.

• Capability to collaborate within structured delivery teams and adhere to SOW-defined scopes and timelines.

• Familiarity with AWS agent frameworks and tools like Strands SDK, Amazon Bedrock AgentCore, and Amazon Quick.

• Practical experience with Amazon SageMaker, including training jobs, inference endpoints, Pipelines, and model registry.

• Experience in executing AWS migration programs.

• Knowledge of AWS Landing Zones, Control Tower, and multi-account governance.

• Understanding of ML evaluation methods, such as confusion matrices, confidence calibration, ECE, and F1 disaggregation.

• Awareness of security reviews and threat modeling for AI systems.

• AWS certifications like ML Specialty or Solutions Architect Associate, or an equivalent qualification.

• Background in delivering services within a consultancy or Professional Services setting.

🏝️ Benefits

• Competitive salary and performance-based bonuses.

• Opportunities for professional growth and development.

• Flexible work arrangements and a supportive work environment.

• Access to the latest technologies and tools in the industry.

• Comprehensive health and wellness programs.