Senior AWS Engineer – AI/ML

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

📋 Description

• Design 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 as Infrastructure as Code (IaC) using Terraform, which includes Lambda, EventBridge, DynamoDB, S3, SageMaker Pipelines, and CloudWatch dashboards.

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

• Set up MLOps pipelines encompassing model registry, deployment automation, drift monitoring, active learning loops, and retraining triggers.

• Implement AWS Landing Zone and multi-account frameworks utilizing Control Tower, Organizations, and Terraform.

• Assist in migration and modernization projects, which include server migrations, database migrations, networking, and constructing application platforms.

• Create and develop 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.

⛳️ Requirements

• Over 3 years of hands-on experience in building solutions on AWS, specifically for AI and ML workloads (such as Amazon Bedrock, SageMaker, or comparable cloud ML platforms).

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

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

• Strong knowledge of EC2, VPC, Lambda, EventBridge, DynamoDB, S3, IAM, CloudWatch, and RDS.

• Experience in Infrastructure as Code with Terraform, CloudFormation, or CDK.

• Proven track record in building CI/CD pipelines and automated testing processes.

• Capability to work within structured delivery teams while adhering to SOW-defined scope and timelines.

• Knowledge of AWS agent frameworks and tools, including Strands SDK, Amazon Bedrock AgentCore, or Amazon Quick.

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

• Background in delivering AWS migration programs.

• Familiarity with AWS Landing Zones, Control Tower, and multi-account governance.

• Understanding of ML evaluation methodologies, including confusion matrices, confidence calibration, ECE, and F1 disaggregation.

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

• AWS certifications such as ML Specialty or Solutions Architect Associate, or equivalent qualifications.

• Experience working in a consultancy or Professional Services environment.

🏝️ Benefits

• Competitive compensation package.

• Opportunities for professional growth and development.

• Flexible working arrangements.

• Access to the latest technologies and tools.

• Collaborative and innovative work environment.