AWS AgentCore Platform Engineer - 67417

Hitachi Automotive Systems Americas, Inc.; Reading (Berks County); On-site; USD 120,000 - 180,000; Full time

Job summary

Hitachi Digital Services is seeking a Senior AWS Platform Engineer to build and operate enterprise AI platforms. You’ll partner with cloud architects, AI engineers, and security specialists to create secure, scalable, observable AI platforms with a strong governance model.

The role emphasizes designing observability, cost governance, and automation using AWS Bedrock, AgentCore, MCP servers, and Terraform. Collaboration across teams in an Agile environment is essential.

Qualifications

• 8+ years of experience in Platform Engineering, DevOps, SRE, or Cloud Infrastructure Engineering.
• Strong expertise in AWS cloud services including IAM, CloudWatch, Lambda, Bedrock.
• Hands-on observability and distributed tracing using Dynatrace, Jaeger, Honeycomb, OpenTelemetry.
• Experience designing Infrastructure-as-Code using Terraform.
• Strong background building CI/CD pipelines in enterprise environments.
• Experience in Agile teams using Microsoft Teams and Confluence.

Responsibilities

• Design and implement enterprise observability for AI agent ecosystems on AWS Bedrock and MCP servers.
• Assess and optimize CloudWatch, X-Ray, Bedrock logging, and tracing capabilities.
• Develop distributed tracing frameworks for AI workloads and build structured logging frameworks.
• Design post-deployment validation pipelines for AI agents and MCP servers.
• Architect cost visibility and governance frameworks across AI workloads.
• Build dashboards and reporting solutions for AI platform cost tracking.

Skills

Platform Engineering

DevOps

SRE

Cloud Infrastructure

AWS Cloud Services

Observability

Distributed tracing

Terraform

CI/CD pipelines

Agile teamwork

Tools

Dynatrace

Jaeger

Honeycomb

OpenTelemetry

Terraform

CI/CD tools

Confluence

Job description

Function Cloud & Data Engineering Our Company

We’re Hitachi Digital Services, a global digital solutions and transformation business with a bold vision of our world’s potential. We’re people-centric and here to power good. Every day, we future-proof urban spaces, conserve natural resources, protect rainforests, and save lives. This is a world where innovation, technology, and deep expertise come together to take our company and customers from what’s now to what’s next. We make it happen through the power of acceleration. Imagine the sheer breadth of talent it takes to bring a better tomorrow closer to today. We don’t expect you to ‘fit’ every requirement – your life experience, character, perspective, and passion for achieving great things in the world are equally as important to us.

Job description Meet Our Team Join a forward-thinking Engineering and AI Platform team focused on building the next generation of enterprise AI solutions. Our team is pioneering agentic AI ecosystems powered by AWS Bedrock, AgentCore, MCP servers, and modern cloud-native technologies. As a Senior AWS AgentCore Platform Engineer, you'll work alongside Cloud Architects, AI Engineers, Platform Engineers, and Security specialists to establish scalable, secure, and observable AI platforms. You'll play a critical role in defining the operational foundation that enables enterprise teams to deploy AI agents with confidence, governance, and efficiency. This is an exciting opportunity to shape enterprise AI infrastructure, drive innovation in LLMOps, and influence platform standards across multiple business units.

What You’ll Be Doing

AI Platform Observability & Reliability

• Design and implement enterprise-grade observability solutions for AI agent ecosystems built on AWS Bedrock, AgentCore, and MCP servers.
• Assess and optimize CloudWatch, X-Ray, Bedrock logging, and AgentCore tracing capabilities against agentic workflow requirements.
• Conduct gap analyses and implement observability solutions using Dynatrace and other monitoring platforms.
• Develop distributed tracing frameworks for AI workloads, including: LLM decision paths Tool invocations Sub-agent interactions MCP server communications Build structured logging frameworks to support troubleshooting, governance, and performance optimization.
• Design post-deployment validation pipelines for AI agents and MCP servers, including deployment health monitoring and registration verification.

Cost Governance & Optimization

• Architect cost visibility and governance frameworks across AI workloads.
• Extend cloud tagging strategies to include agent runtimes, vector databases, MCP services, and Bedrock token consumption.
• Develop cost allocation models to provide spending transparency by team, department, and application.
• Build dashboards and reporting solutions for AI platform cost tracking and forecasting.
• Configure AWS Budgets, automated alerts, anomaly detection, and optimization recommendations.
• Deliver automated cost reporting through Microsoft Teams and email channels.

Monitoring & Incident Management

• Define enterprise monitoring standards and alerting frameworks across AI platform services.
• Create and manage P1-P4 alerting strategies covering: Deployment failures Runtime exceptions Tool invocation errors MCP connectivity issues
• Integrate monitoring and notification workflows with Microsoft Teams and email.
• Develop operational runbooks and self-service documentation within Confluence.
• Evaluate AWS-native and third-party monitoring solutions and recommend target-state architectures.

Security & Platform Governance

• Assess IAM architectures and multi-team access models for enterprise-scale AI environments.
• Design Attribute-Based Access Control (ABAC) frameworks to support secure multi-team isolation.
• Evaluate Cedar policy engine capabilities within AgentCore for fine-grained authorization models.
• Develop reusable Terraform modules to enforce governance, security, and compliance standards.
• Identify scalability risks and implement secure platform design patterns for enterprise AI adoption.

Platform Engineering & Automation

• Build and maintain Infrastructure-as-Code solutions using Terraform.
• Design and enhance CI/CD pipelines supporting AI platform deployments.
• Collaborate with engineering, security, architecture, and business stakeholders in Agile environments.
• Drive platform standardization, automation, and operational excellence initiatives.

What You’ll Bring to the Team

Required Qualifications

• 8+ years of experience in Platform Engineering, DevOps, Site Reliability Engineering (SRE), or Cloud Infrastructure Engineering.
• Strong expertise in AWS cloud services including: IAM CloudWatch AWS Lambda AWS Bedrock Cloud-native monitoring and governance services
• Hands-on experience implementing observability and distributed tracing solutions using tools such as: Dynatrace Jaeger Honeycomb OpenTelemetry
• Experience designing and managing Infrastructure-as-Code using Terraform.
• Strong background building and maintaining CI/CD pipelines in enterprise environments.
• Experience working in Agile teams utilizing Microsoft Teams, Confluence, and modern collaboration tools.

Preferred Qualifications

• Experience supporting AI, Generative AI, or LLM-based platforms.
• Familiarity with AgentCore, LangChain, LangFuse, LiteLLM, MCP servers, or similar AI orchestration frameworks.
• Understanding of LLM lifecycle management, prompt execution flows, token consumption tracking, and AI workload optimization.
• Knowledge of cloud cost management, FinOps practices, and governance frameworks.
• Experience designing enterprise-scale security architectures using ABAC and policy-based authorization models.
• Strong analytical and problem-solving skills with