Job Summary
The ideal candidate will have experience with Generative AI/LLM technologies, AWS, Python, DevOps, CI/CD, Terraform, and application security. This position will work within an established architecture under the guidance of Lead and Principal Engineers and will participate in a rotating 24/7 operational support schedule. Key Responsibilities
Operate and monitor an LLM-based code vulnerability detection solution running on AWS Bedrock.
Monitor scanner health, model invocation errors, job execution, token usage, and cost consumption.
Monitor and troubleshoot scanning pipelines integrated with GitHub and Jenkins.
Investigate failed jobs, queue backlogs, pipeline failures, and environment issues.
Execute documented operational runbooks and escalate issues appropriately.
Perform structured shift handoffs and document open issues, changes, and escalations.
Apply patches, dependency updates, and configuration changes through change-management processes.
Monitor Splunk dashboards and alerts for scanner health, coverage, and throughput.
Execute evaluation/testing harnesses and identify regressions in vulnerability-detection performance.
Implement assigned engineering changes within the established architecture.
Make guided updates to Terraform configurations and CI/CD pipelines.
Develop and modify Python scripts and automation.
Maintain runbooks, operational procedures, and technical documentation.
Support containerized environments using AWS ECS / ECS Fargate.
Participate in Agile engineering activities and follow security, compliance, and regulatory requirements.
Provide rotating 24/7 coverage, including nights, weekends, and holidays.
Required Skills
1+ year of GenAI / LLM-related development or technical operations experience.
1+ year of information security, infrastructure, software engineering, or technical operations experience.
Hands-on knowledge of AWS, including AWS Console, CLI, IAM, and CloudWatch.
Experience with Amazon Bedrock or equivalent hosted LLM platforms.
Experience with Python scripting and automation.
Strong understanding of DevOps and CI/CD practices.
Experience with Jenkins, GitHub, and CI/CD pipelines.
Experience reading and modifying Terraform.
Understanding of application security and common vulnerability classes.
Experience with containers/containerization, preferably AWS ECS or ECS Fargate.
Ability to troubleshoot production issues and follow technical runbooks.
Strong written and verbal communication skills.
Ability to work independently during off-hours shifts.
Preferred Skills
AWS Bedrock / LLM / Generative AI experience.
AWS ECS Fargate and Docker/container experience.
Splunk dashboards, searches, and alerting.
Linux systems administration.
ServiceNow or similar incident/change-management tools.
DevSecOps and application security experience.
Agile/Scrum experience.
Experience in financial services or regulated environments.