• Design, build, and maintain production Python services that power AI features with reliability and performance • Stay on top of emerging frameworks and Python ecosystem - evaluate new tools that improve our capabilities • Work cross-functionally with ML engineers, platform engineers, and product to ensure services meet real needs • Balance experimentation with production excellence - prototype quickly with new techniques while ensuring production reliability • Write comprehensive tests and documentation that make systems understandable and maintainable • Mentor engineers on Python best practices, service design, and LLM integration patterns

• Build user experiences, APIs, and data handling processes in our TypeScript application using React and Remix frameworks • Collaborate with a passionate team to solve customer problems and maintain performance and quality standards

• You will work closely with customer service, product, and other engineering teams to develop new network data observability & intelligence features. • Act as a lead Individual Contributor to improve Query services, focusing on query speeds, throughput, and latency • Collaborate with other engineering, support, and sales teams to drive platform-wide query standards. • Solve high-visibility, challenging engineering problems related to the data-intensive query engine.

• AI-Accelerated Development: Integrate AI assistants (e.g., Cursor, GitHub Copilot) into your daily workflow for rapid code generation, debugging, and complex problem-solving. • High-Transaction Systems: Design and implement scalable backend services using .NET Core 6+ capable of handling thousands of concurrent users. • Microservices Architecture: Build and optimize distributed systems with a focus on high availability, utilizing Event-Driven architectures and message queuing (Kafka, RabbitMQ, or Azure Service Bus). • AIDLC Testing: Achieve a mandatory 97% code coverage ratio by leveraging AI to generate comprehensive unit, integration, and end-to-end tests. • Performance Tuning: Optimize SQL (SQL Server/PostgreSQL) and NoSQL (MongoDB/Redis) schemas and queries to ensure peak application performance. • Technical Governance: Participate in rigorous code reviews focused on performance, observability, and adherence to "Simple Code" standards.