Senior AWS Agentcore Platform Engineer

Senior AWS Agentcore Platform Engineer

Position Type:
Contract to hire after initial 6 months

Location:

Reading, PA or Exton, PA (Hybrid 2-3 days a week from office)

Job Description:

• Gap Analysis:
  Assess AWS Cloud Watch, X-Ray, Bedrock logging, and Agent Core traces against agentic workflow requirements; produce a comprehensive gap analysis and lead the setup of observability within Dynatrace.
• Validation Pipelines:
  Design and implement post-deployment validation pipelines for agents and Model Context Protocol (MCP) servers, ensuring deployment health and successful tool registration.
• Tracing & Logging:
  Implement distributed tracing and structured logging to capture LLM decision logic, tool selections, sub-agent calls, and MCP interactions.
• Architecture Strategy:
  Evaluate Lang Fuse and LiteLLM proxies against AWS-native solutions; deliver a target-state observability architecture recommendation.

• Taxonomy Expansion:
  Extend tagging taxonomy to capture costs across agent runtimes, MCP servers, vector databases, and Bedrock token consumption per namespace.
• Cost Modeling:
  Design a granular cost visibility model to aggregate expenses for agents, MCPs, and LLM tokens by team and department.
• Dashboards & Alerting:
  Build Cloud Watch (or equivalent) dashboards for per-team spending; configure AWS Budgets with proactive alerting thresholds.
• Automation:
  Automate cost reporting via email and Microsoft Teams, incorporating anomaly detection rules to identify spend spikes.

• Alerting Framework:
  Define and implement P1–P4 alerting rules covering deployment failures, runtime errors, tool invocation failures, and MCP connectivity issues.
• Incident Integration:
  Integrate alert notifications with Microsoft Teams and email, utilizing resource ownership tags for intelligent routing.
• Operational Excellence:
  Author detailed runbooks for every alert; publish and maintain these in Confluence to facilitate developer self-service resolution.
• Stack Evaluation:
  Compare AWS-native vs. third-party monitoring stacks to deliver a long-term recommendation aligned with the broader observability architecture.

• Risk Assessment:
  Evaluate current IAM and tagging strategies for multi-team isolation; identify scalability gaps and potential security risks.
• Policy Engines:
  Assess the Cedar policy engine (Agent Core) for fine-grained tool access control and document gaps for enterprise-scale deployment.
• Identity Architecture:
  Design a scalable Attribute-Based Access Control (ABAC) identity model to ensure multi-team isolation without IAM policy sprawl; deliver production-ready Terraform modules.