AWS Architect

MARICI Solutions GmbH; Reading (Berks County); Hybrid; USD 100,000 - 150,000; Full time

Job summary

MARICI Solutions GmbH in Reading, PA (hybrid) seeks an experienced AWS ML/AI engineer for a long-term contract. The role centers on building and managing end-to-end ML pipelines using AWS SageMaker Unified Studio, Terraform IaC, and Bedrock tools.

Candidates with proficiency in Python, MLOps, IAM security, and multi-agent orchestration will excel. Certifications such as AWS MLS-C01 or AI Practitioner are highly preferred. Travel to Reading is required on a regular basis.

Qualifications

• Hands-on Python development (3.11+) for robust applications and agentic logic.
• Extensive experience with AWS SageMaker Unified Studio (SMUS) and MLOps for end-to-end ML lifecycle.
• Production-level Terraform IaC to provision AWS services including Bedrock, DynamoDB, Lambda.
• CI/CD and DevOps practices for cloud-native apps and MLOps workflows.
• Deep experience with AWS IAM and secure service communications.
• Familiarity with AWS Bedrock AgentCore, including Agent Runtime, Memory, Identity, and Tool Gateway.
• Experience with multi-agent orchestration frameworks (LangGraph, strands, etc.).
• Understanding of MCP (Model Context Protocol) and modern tool/API integration for AI agents.
• Optional AWS professional certifications (AI Practitioner or MLS-C01) preferred.

Responsibilities

• Develop and maintain ML pipelines and automation for model training and deployment.
• Configure and manage end-to-end inference endpoints in SMUS and related tools.
• Implement IaC using Terraform to provision AWS services including Bedrock components.
• Maintain secure, scalable CI/CD pipelines for cloud-native ML applications.
• Collaborate on MLOps workflows and secure service communications (IAM).

Skills

Python

AWS SageMaker

MLOps

CI/CD

AWS Bedrock

Tools

Terraform

DynamoDB

Lambda

IAM

Job description

Location : Reading, PA (hybrid) Long Term Contract Job description is below, and the key points are they must have direct experience with AWS SageMaker, Terraform, some AI familiarity is nice to have in particular AWS Bedrock, and they must be in Reading, PA or close enough to travel there on a regular basis. Please include any of these certifications in your search requirements, along with Terraform and SageMaker; this might help filter for the right candidate.

• AWS Certified Machine Learning Engineer - Associate
• AWS Certified AI Practitioner
• AWS Certified Machine Learning - Specialty (MLS-C01)

Here is the revised JD

• Python (3.11+): Hands-on experience building robust applications and agentic logic.
• Amazon SageMaker Unified Studio (SMUS) & MLOps: Hands-on experience with SMUS to manage the end-to-end ML lifecycle. This includes automating model training, registering models in the centralized registry, and configuring real-time/asynchronous inference endpoints within the SMUS ecosystem.
• Infrastructure as Code (IaC):Production-level expertise using Terraform to provision AWS services, including Bedrock Agents, Knowledge Bases, DynamoDB, Lambda, etc.
• CI/CD & DevOps: Proven track record in building and maintaining automated deployment pipelines for cloud-native applications and MLOps workflows.
• AWS Security & Identity: Deep experience with IAM for fine-grained permissions and secure service communication.
• AWS Bedrock AgentCore : Familiarity with the latest ecosystem, specifically the Agent Runtime, Memory, Identity, and Tool Gateway layers.
• Multi-Agent Orchestration: Experience building or enabling collaborative systems using frameworks like LangGraph, strands, etc.
• Model Context Protocol (MCP): Strong understanding of MCP and modern tool/API integration patterns for AI agents.
• AWS Certification (Optional): Holding one or more AWS Professional-level certifications - specifically the AWS Certified AI Practitioner or AWS Certified Machine Learning - Specialty is highly preferred and considered a strong plus.
• Continuous Learning: Willingness to learn emerging AI technologies, frameworks, and evolving cloud services.