AWS Solutions Architect – AI Implementations

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

📋 Description

• Designing comprehensive AWS architectures for AI and GenAI implementations across various client projects.

• Facilitating architecture discovery workshops and conducting Well-Architected Framework reviews with client teams.

• Choosing and configuring the appropriate AWS AI/ML services for each specific use case — including Bedrock, SageMaker, Comprehend, Textract, and more.

• Establishing IaC standards and evaluating infrastructure implementations by engineering teams.

• Providing guidance on data architecture — focusing on ingestion, storage, transformation, and access patterns optimized for AI workloads.

• Collaborating with client security and compliance teams to ensure architectures adhere to regulatory and enterprise standards.

• Assisting in pre-sales activities and solution development — including proposals, effort estimations, and technical presentations for clients when necessary.

• Mentoring cloud engineers within the delivery team and conducting architecture and code reviews.

• Keeping up-to-date with the AWS AI/ML service roadmap and advising clients on relevant emerging capabilities.

⛳️ Requirements

• Demonstrated AWS architecture experience at a senior or lead level (5+ years of hands-on experience across multiple production environments).

• Practical experience in designing and implementing AI/ML solutions on AWS — including Amazon SageMaker, Amazon Bedrock, or equivalent managed AI services.

• In-depth understanding of AWS core services: compute (EC2, ECS, EKS, Lambda), storage (S3, EFS), databases (RDS, DynamoDB, Aurora), and networking (VPC, API Gateway, CloudFront).

• Experience with Infrastructure as Code — such as Terraform, AWS CDK, or CloudFormation — with a proven track record in production, not just theoretical knowledge.

• Familiarity with data architecture patterns tailored for AI workloads: data lakes, streaming pipelines, feature stores, and vector databases.

• Security-first design approach — including IAM, VPC design, encryption, and compliance with GDPR and common enterprise security frameworks.

• Capability to engage directly with clients: translating business requirements into architectural decisions and effectively communicating them to both technical teams and senior stakeholders.

• Proficiency in English at B2 level or above (working language across international delivery teams and clients).

• NICE TO HAVE: AWS certification — Solutions Architect Professional, Machine Learning Specialty, or equivalent (valued but not mandatory).

• Experience with GenAI application architecture: LLM integration, RAG (Retrieval-Augmented Generation), and agentic AI frameworks (LangChain, LangGraph) operating on AWS infrastructure.

• MLOps experience — including model deployment pipelines, monitoring, drift detection, and model versioning (SageMaker Pipelines, MLflow, etc.).

• Multi-account AWS architecture experience: AWS Organizations, Control Tower, and landing zones.

• Expertise in cost optimization — including FinOps practices, Reserved Instances, Savings Plans, and rightsizing for AI/GPU workloads.

• Background in regulated industries: financial services, healthcare, or public sector — along with the associated compliance requirements.

• Experience with containerized AI workloads: Docker, Kubernetes (EKS), and Helm.

• Knowledge of observability and monitoring tools: CloudWatch, AWS X-Ray, and OpenTelemetry.

🏝️ Benefits

• Options for remote work.