AWS AgentCore Platform Engineer

Position : AWS AgentCore Platform Engineer

Location : Reading, PA (Hybrid 2-3 days/wk at client office

6-12+ months contract

• 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.

Please check if the next candidate has some experience with at least 50% of below items:

• Implementation of Agents on Agentcore runtime

• Implementation of Agentic SDLC in Agentcore

• Understanding of Strands or any other Agentic AI framework like Langraph, Langchain or Crew AI

• Implementation of Bedrock Knowledge Base

• Implementation of Knowledge Graph

• Implementation of MCP servers in Agentcore

• Implementation of Agentcore Gateway

• Implementation of Agentcore Identity

• Implementation of Agentic AI Observability

• Implementation of Agentcore Evaluations

• Implementation of AWS Bedrock

• Implementation of AWS Bedrock Inference Profile

• Implementation of AWS Sagemaker

• AWS Services (Cloud) in General

• Terraform

Observability

Assess CloudWatch, X-Ray, Bedrock logging, AgentCore traces vs. agentic workflow requirements; produce gap analysis, Setup observability in Dynatrace

Design post-deployment validation pipeline for agents & MCP servers (deployment health + tool registration checks)

Implement distributed tracing & structured logging: LLM decisions, tool selections, sub-agent calls, MCP interactions

Evaluate LangFuse / LiteLLM proxy vs. AWS-native; deliver target-state observability architecture recommendation

Cost Tracking & TCO

Extend tagging taxonomy to cover agent runtimes, MCP servers, vector DBs, Bedrock token consumption per namespace

Design cost visibility model: aggregate agent, MCP, vector DB, and Bedrock token costs per team/department

Build CloudWatch (or equivalent) dashboards for per-team spend; configure AWS Budgets with alerting thresholds

Automate cost reports delivered via email / Microsoft Teams; implement anomaly detection rules

Monitoring & Alerting

Define P1–P4 alerting rules: deployment failures, runtime errors, tool invocation failures, MCP connectivity issues

Integrate alert notifications to Microsoft Teams channels and email; route by resource ownership tags

Author runbooks linked to every alert; publish in Confluence for developer self-service resolution

Evaluate AWS-native vs. third-party monitoring stack; deliver recommendation aligned to observability architecture

Security & Access Control

Assess current IAM + tagging approach for multi-team isolation; identify scalability gaps and risks

Evaluate Cedar policy engine (AgentCore) for fine-grained tool access control; document enterprise-scale gaps

Design scalable ABAC-based identity model for multi-team isolation without IAM policy sprawl; deliver Terraform modules