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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Platform Engineer - **Company:** The Depository Trust & Clearing Corporation - **Location:** United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Amazon Elastic Compute Cloud, Amazon S3, Systems Engineering, Big Data, Complex Networks, Computer Programming, Data Security, Data Sharing, Distributed Data Store, Distributed Systems, Internet Hosting Service, Identity and Access Management, Subnetting, Network Security, Machine Learning, Azure Machine Learning, Data Logging, S3 Bucket, Autoscaling, Snowflake, Multi-Agent Systems, Reliability of Systems, Amazon Virtual Private Cloud (VPC), Infrastructure Automation Frameworks, AWS Glue, Machine Learning Operations, Virtual Agents, Functional Programming, Cloudwatch, Terraform, Splunk, Amazon Elastic Mapreduce (EMR), Jenkins - **Published:** June 4, 2026 - **Apply:** https://www.dice.com/job-detail/4e8998d0-ea5b-4a4f-8d6b-0f7307eac31d ## About the Role * Minimum of 4 years of related experience * Bachelor's degree preferred or equivalent experience ## Description The Systems Engineering family is responsible for the entire technical effort to evolve and verify solutions that satisfy client needs. The primary focus is centered on reducing risk and improving the efficiency, performance, stability, security, and quality of all systems and platforms. The Platform Hosting & Engineering role specializes in the development, implementation, and support of all distributed, mainframe, and network hosting services across the firm. Responsible for the installation, configuration, programming, and support of operating systems, complex networks, and distributed environments, deploying solutions to increase overall system reliability across the firm., * Design, build, and maintain scalable AI/ML platforms using AWS services including SageMaker, Amazon Bedrock, Bedrock Agent Core, Amazon Q Developer and Kiro. * Manage and optimize AWS EMR clusters for large-scale data processing, ensuring efficient resource utilization and high performance. * Develop and maintain MLOps pipelines for model training, validation, and deployment. Implement Amazon Bedrock capabilities including Guardrails and Knowledge Bases to enable secure use of foundation models. * Design and manage AI agent infrastructure using Bedrock Agent Core, including agent orchestration, memory, gateway, and runtime components for enterprise-scale deployments. * Manage and maintain AWS Athena infrastructure, ensuring availability, performance, and proper configuration for analytical workloads. * Implement cloud automation and infrastructure-as-code using Terraform, with CI/CD pipelines managed through Jenkins. * Work with AWS services including VPC, Subnets, EC2, IAM, Security Groups, ECS, S3, ELB, Auto Scaling, Lambda, AWS Glue, Athena, EMR, and ADX to support platform and infrastructure operations. * Configure SageMaker environments with network and security rules including VPC peering, endpoint creation, and security group configurations Perform system upgrades and maintenance for distributed data platforms across multiple AWS accounts. * Implement centralized logging, monitoring, and compliance reporting for AI/ML systems Collaborate with governance and risk teams to ensure compliance and approval of AI/ML models. * Enable secure data access and governance across accounts using data-sharing and access control mechanisms. * Deploy machine learning models using AWS SageMaker, enabling predictive analytics and data-driven decision-making. * Automate infrastructure provisioning using Terraform for SageMaker resources (KMS keys, S3 buckets, etc.). * Configure cross-account integrations for Snowflake across all environments Create customized CloudWatch alarms and configure log ingestion pipelines (CloudWatch to Splunk). ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [How we built an AI-powered code reviewer in 80 hours](https://www.wearedevelopers.com/videos/1511-how-we-built-an-ai-powered-code-reviewer-in-80-hours) - [The Road to MLOps: How Verivox Transitioned to AWS](https://www.wearedevelopers.com/videos/1050-the-road-to-mlops-how-verivox-transitioned-to-aws) - [Our journey with Spring Boot in a microservice architecture](https://www.wearedevelopers.com/videos/511-our-journey-with-spring-boot-in-a-microservice-architecture) - [Enterprise-Cloud-Native - Fast-Paced Development & Deployment in a Highly Secure Banking Environment](https://www.wearedevelopers.com/videos/671-enterprise-cloud-native-fast-paced-development-deployment-in-a-highly-secure-banking-environment) - [Tips, Techniques, and Common Pitfalls Debugging Kafka](https://www.wearedevelopers.com/videos/838-tips-techniques-and-common-pitfalls-debugging-kafka) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [7 Cloud Computing Trends Coming in 2025 for Developers](https://www.wearedevelopers.com/magazine/412-7-cloud-computing-trends-coming-in-2025-for-developers) - [Best Paying Jobs in Technology](https://www.wearedevelopers.com/magazine/256-best-paying-jobs-in-technology) - [How We Built a Worry-Free System That Runs for 10+ Years – And What We’d Do Again](https://www.wearedevelopers.com/magazine/751-how-we-built-a-worry-free-system-that-runs-for-10-years-and-what-we-d-do-again) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Top-Paying Tech Jobs (with Salaries)](https://www.wearedevelopers.com/magazine/372-top-paying-tech-jobs-with-salaries)