Cloud Engineer

About the Role

The AI Agent platform team builds the cloud platform for AI agents that hold natural voice and chat conversations and take actions in business systems through APIs. We build and run the real-time services underneath: low-latency streaming services that hold a live, two-way session with each user, stream audio and messages between services, and integrate with external systems, at enterprise scale across multiple regions.

Key Responsibilities

• Build and extend real-time backend services for the AI Agent platform in Java (Java 21, Quarkus) and Python, for both voice and chat conversations.
• Implement platform features such as long-lived streaming sessions over gRPC and WebSockets, event pipelines on Kafka, session state in Redis and durable data in PostgreSQL, and integrations with customer and partner systems through REST APIs and webhooks.
• Follow spec-driven development: write a proper spec (scope, API/Protobuf contract changes, data and state model, failure handling and test plan), get it reviewed, then build and test against it.
• Use AI coding tools (such as GitHub Copilot, Cursor, ChatGPT or Codex) for implementation, tests, debugging and documentation, while owning the correctness, security and quality of everything merged.
• Write code that holds up in real time: correct timeouts, retries, cancellation and backpressure on streaming paths, bounded per-session resources, and measurable gains in end-to-end latency.
• Write unit, integration and functional tests, and extend the team’s load and chaos test suites and release gates.
• Ship through Docker, Kubernetes and CI/CD pipelines, and instrument every new code path with metrics, traces and dashboards (OpenTelemetry, Grafana).
• Support what you build in production: triage issues across the service, data, network and integration layers, find the root cause and land a lasting fix.
• Work closely with product management, UX, SRE, security and the product teams that use the platform.

Requirements & Tech Stack

• Strong hands-on Java (Java 17 or later): built and shipped production microservices and REST APIs with Quarkus, Spring Boot or a similar framework.
• Strong hands-on Python: write production-quality Python for services, tooling or test automation.
• Hands-on experience deploying and running services with Docker and Kubernetes on a public cloud (AWS, Azure or Google Cloud).
• Spec-driven development: write a proper spec before implementing a non-trivial change (scope, API contract, data model, edge cases, test plan) and then build and test against it.
• AI-assisted development: use AI coding tools such as GitHub Copilot, Cursor, ChatGPT or Codex in daily work, and review, test and correct generated code.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering or a related field, or equivalent practical experience.

Preferred Qualifications (Good To Have)

• Quarkus, and modern Java 21 features such as records, pattern matching and virtual threads.
• gRPC and Protocol Buffers, WebSockets, or other streaming APIs.
• Kafka, Redis, PostgreSQL or MongoDB.
• AWS services such as EKS, S3 and RDS, and delivery tooling such as Helm, Terraform, Argo CD, Jenkins or GitHub Actions.
• Observability with OpenTelemetry, Prometheus, Grafana, Jaeger or Splunk.
• Resilience patterns such as circuit breakers, bulkheads and idempotent retries (for example SmallRye Fault Tolerance or Resilience4j).
• Real-time communications: WebRTC, SIP or audio and media streaming.
• Load and chaos testing with k6, Locust, Gatling or JMeter.
• Application and API security: OWASP Top 10, OAuth 2.0 and JWT, secrets management and tenant isolation.
• TypeScript, React or Next.js for internal tools and test clients.
• Experience building shared platforms or APIs used by other product teams.