AWS AgentCore Platform Engineer

Location: Reading PA (Hybrid 2-3 days a week)

Note: AgentCore experience is must.

Job Description: 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.