The Senior Product Owner/Scrum Master will own the product vision, roadmap, and backlog while facilitating Scrum ceremonies to ensure team alignment. They will lead a multi-team program by coaching self-organization, removing impediments, and maintaining clear communication with stakeholders.
The engineer will design and build end-to-end AI applications using Python, FastAPI, and React on Google Cloud. Responsibilities include implementing multi-agent workflows, managing data models, and deploying containerized services to Cloud Run.
The engineer will design and implement core domain microservices on Google Cloud, including licensing, case management, and payment processing. They will also own the platform's API surface, ensuring stable contracts for mobile, frontend, and integration teams.
The engineer will architect, build, and secure a FedRAMP High-compliant Google Cloud Platform landing zone for a multi-department enterprise migration. They will also manage the consolidation of legacy systems into a unified, IaC-managed environment while ensuring end-to-end network security.
The engineer will define and maintain the test strategy and automated test suites for web, API, and mobile platforms. They will also integrate these suites into CI/CD pipelines and support performance testing and UAT cycles.
The engineer will design and implement Java-based microservices on Google Cloud to support a professional licensing and regulatory compliance platform. They will also build external integration layers and manage asynchronous event flows to ensure seamless communication with state and federal systems.
Develop and maintain an offline-first field inspection tablet application using React Native and Expo for iOS and Android. Manage end-to-end feature delivery, including data synchronization, hardware integration, and secure authentication.
The Lead Software Engineer will own the backend architecture and integration layer for a government licensing platform on Google Cloud. They will lead the backend team, set engineering standards, and remain hands-on with production code throughout the project lifecycle.
The engineer will build and extend full-stack features across React, Node.js, and Go services while managing backend API integrations. They are also responsible for refactoring legacy codebases and implementing secure authentication and authorization protocols.
You will build and maintain an AI-driven metadata engine and automated ownership reassignment logic within an enterprise platform. The role involves refactoring legacy code, managing agent and MCP inventory, and delivering features through agile sprints.
You will convert standard operating procedures into automation routines and optimize the daily efficiency of systems and cloud management. Additionally, you will serve as the primary resource for providing automation runbooks for core systems, Windows server management, and SaaS application platforms.
The Site Reliability Engineer will maintain production systems, manage on-call rotations, and improve infrastructure through automation. They will also design scalable core infrastructure and debug complex production issues across the stack.
You will be responsible for optimizing GCP cloud spend through FinOps practices and managing the Kubernetes platform lifecycle. Additionally, you will automate infrastructure provisioning and support engineering teams using AI-assisted development workflows.
Site Reliability Engineers are responsible for maintaining production systems, ensuring service availability, and automating infrastructure tasks. They participate in on-call rotations to resolve incidents and improve system scalability through sound engineering practices.
Design, write, and maintain Python tooling to automate, provision, and audit global network infrastructure. Operate and scale data center fabrics and backbone networks while participating in a 24x7 on-call rotation to ensure system reliability.
You will design, build, and deploy full-stack application features using React, Node.js, and PostgreSQL while managing cloud infrastructure on GCP. Additionally, you will maintain CI/CD pipelines and ensure high-quality code through comprehensive unit, integration, and end-to-end testing.
The role involves owning the end-to-end quality of an agentic AI platform, from initial test planning to final release. Responsibilities include writing manual test cases and building automated coverage for conversational flows and AI decision-making.
Act as the primary administrator and architect for the BigPanda ecosystem to transform telemetry data into automated operational insights. Design ingestion pipelines from GCP and integrate monitoring tools with downstream ITSM workflows to reduce MTTR.
Design and maintain enterprise observability frameworks and alerting ecosystems across multi-cloud and hybrid environments. Automate infrastructure using IaC and optimize system performance through SRE best practices like SLIs and SLOs.
