Senior AWS Agentcore Platform Engineer (Client: )

Senior AWS Agentcore Platform Engineer (Client: ) IRC: IRC292142 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: Observability & Distributed Tracing Gap Analysis: Assess AWS CloudWatch, X-Ray, Bedrock logging, and AgentCore 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 LangFuse and LiteLLM proxies against AWS-native solutions; deliver a target-state observability architecture recommendation. Cost Tracking & TCO (Total Cost of Ownership) 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 CloudWatch (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. Monitoring & Incident Management 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. Security & Governance 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 (AgentCore) 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. #J-18808-Ljbffr