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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr. Software Engineer, Platform (Hybrid) - **Company:** American Medical Association - **Location:** Chicago, IL, United States - **Experience:** Expert - **Salary:** $115,500.0 - $151,000.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Confluence, JIRA, Bash Shell, Cloud Computing, Cloud Engineering, Software Quality, Code Review, Continuous Integration, Data Control, Programming Tools, Amazon DynamoDB, Monitoring of Systems, HP Systems Insight Manager, Python (Programming Language), Software Engineering, Software Systems, Systems Integration, Data Processing, Infrastructure Automation Frameworks, Information Technology, Deployment Automation, Atlassian Tools, Data Analytics, AWS Fargate, Bitbucket, Terraform, Dynatrace, Serverless Computing - **Published:** September 5, 2026 - **Apply:** https://diversityjobs.com/main/sendform/8/8/28176/1/18194228?backUrl=%2Fcareer%2F18194228%2FSr-Software-Engineer-Platform-Hybrid-Illinois-Chicago ## About the Role 1. Bachelor's degree in Computer Science or Engineering preferred or equivalent work experience and HS diploma/equivalent education required. 2. 5+ years of experience in platform engineering, cloud engineering, software infrastructure, or a related field. 3. Proven experience with AWS services, including Lambda and ECS Fargate, with optional familiarity with RDS, DynamoDB, and DocumentDB. 4. Experience improving development tooling, release processes, or engineering workflows. 5. Analytical skills to evaluate code and platform infrastructure and make data-driven decisions. 6. Self-starter with a demonstrated ability to learn and apply new technologies. 7. Excellent problem-solving capabilities and the ability to work independently or within a team. 8. Strong communication and coaching skills, with the ability to articulate complex technical issues and help teams adopt emerging capabilities effectively. 9. Proactive approach to identifying problems, improvement opportunities, and performance bottlenecks. 10. Experience introducing, evaluating, or supporting AI-assisted development tools within engineering teams. 11. Ability to assess AI use cases in terms of technical value, implementation risk, security, reliability, and measurable outcomes. 12. Experience creating technical standards, reusable implementation guidance, or enablement materials for other engineers. 13. Understanding of the need for data controls, generated-output validation, human review, and operational visibility within AI-assisted workflows. Additional Technical Background 1. Experience operating a full AWS stack, including serverless capabilities and the deployment and scaling of applications on AWS. 2. Familiarity with the Atlassian toolset used for day-to-day work organization, including Jira, Bitbucket, and Confluence. 3. Experience supporting engineering teams through the adoption of new development tools, practices, or platform capabilities. 4. Familiarity with AI coding assistants, model APIs, or similar AI-enabled development capabilities is preferred. 5. Proficiency in Python, Java, Bash, or similar languages used for platform automation and systems integration. 6. Solid understanding and practical knowledge of CI/CD methodologies, particularly Bitbucket pipelines. 7. Experience with observability and monitoring tools such as Dynatrace or similar systems. 8. Strong background in infrastructure as code, preferably Terraform. ## Description As a Sr. Software Engineer, Platform you will play a critical role in improving the stability, observability, scalability, and delivery of AMA's Physician Professional Data, credentialing products portfolio, and commercial products and systems. This role enhances AWS infrastructure, monitoring capabilities, CI/CD pipelines, infrastructure automation, release processes, developer tooling, and approved AI-assisted engineering capabilities to enable efficient software development. The role partners with engineering, product, data, security, and AMA IT to support secure and reliable software delivery. This role also follows established enterprise review and approval processes for technologies and related standards, collaborating with IT, OGC, and Risk Management to ensure alignment with enterprise architecture, security, and data and AI strategy., Platform Engineering - 55% * Implement and maintain observability and monitoring tools, primarily using Dynatrace for performance profiling and application monitoring. * Improve the modularity, consistency, and scalability of code infrastructure. * Develop and maintain CI/CD capabilities using Bitbucket pipelines and related delivery tooling. * Standardize branching, build, release, and deployment strategies across repositories. * Maintain and improve Terraform stacks for efficient infrastructure-as-code practices. * Develop and maintain release and stability dashboards that provide actionable insights into system performance and reliability. * Support and improve code-release processes to ensure repeatable and reliable deployment cycles. * Define and implement standards for stability and observability across DataLabs projects. * Partner with engineering teams to identify platform improvements that reduce development friction and improve delivery outcomes. AI-Assisted Engineering Enablement - 20% * Partner with engineering teams to identify and prioritize AI-assisted use cases across coding, testing, documentation, troubleshooting, code review, operational support, and knowledge discovery. * Evaluate AI development tools and capabilities based on engineering value, usability, security, reliability, maintainability, and supportability. * Develop reusable guidance, examples, and integration patterns, and share knowledge by coaching engineers on effective and responsible use of AI-assisted development capabilities. * Help integrate approved AI capabilities into existing development tools and engineering workflows. * Implement approved practices for data handling, access, generated-output validation, human review, and traceability. * Work with security, architecture, and engineering stakeholders to identify risks and define appropriate controls for AI-assisted workflows. * Gather adoption data and engineering feedback to evaluate whether AI-enabled workflows improve delivery speed, software quality, and developer experience. * Document successful use cases, known limitations, and recommended implementation patterns. * Monitor emerging AI development capabilities and evaluate opportunities aligned with Health Solutions engineering needs. Cloud Infrastructure - 25% * Collaborate with engineering teams to analyze the current state of infrastructure and develop improvement strategies. * Define technology and infrastructure requirements for product-development assets, including cloud-computing needs. * Identify opportunities to adopt new technologies and integrate with additional systems. * Collaborate with AMA IT teams and vendors to select, design, and implement infrastructure. * Evaluate the infrastructure and integration requirements associated with approved AI-assisted development capabilities. * Ensure new platform and AI enablement capabilities can be monitored, maintained, and supported within existing engineering operations. 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