Posted May 4, 2026
Key Responsibilities:
Design and implement components for AI-enhanced tooling to monitor, evaluate, and enhance software behavior with a focus on safety and resilience in distributed systems. - Build and maintain systems utilizing semantic chunking, language model agents, and automated reasoning to support developer workflows with contextual awareness and guidance. - Work closely with cross-functional teams to translate high-level needs into technical designs and robust implementations. - Contribute to safe AI practices by defining interfaces and logic to prevent and detect unsafe code constructs or misconfigurations. - Collaborate with DevOps and CI/CD engineers to integrate quality feedback loops, instrumentation, and runtime guards into build, deploy, and release pipelines. - Participate in design reviews, code reviews, and retrospectives to drive continuous improvement of AI-infused systems. - Investigate issues in distributed environments, propose solutions, and deliver fixes to enhance maintainability, performance, and safety. - Help establish best practices for code health, observability, and monitoring in intelligent pipelines. Qualifications Required:
58 years of software engineering experience with proficiency in languages like Python, Go, or TypeScript. - Strong understanding of distributed system design, asynchronous workflows, and microservices architectures. - Experience or strong interest in AI/ML concepts, particularly in applying models to assist developer tooling or runtime analysis. - Familiarity with modern cloud environments (AWS, GCP, Azure) and container orchestration (e.g., Kubernetes). - Comfortable working with APIs, message buses, and streaming data (e.g., Kafka, Pub/Sub). - Practical knowledge of secure development practices, runtime policy enforcement, and defensible system design. - Experience in integrating or building systems using semantic chunking or structural representations of code/data is a plus. - Excellent collaborator with clear communication skills who contributes to team success. Key Responsibilities:
Design and implement components for AI-enhanced tooling to monitor, evaluate, and enhance software behavior with a focus on safety and resilience in distributed systems. - Build and maintain systems utilizing semantic chunking, language model agents, and automated reasoning to support developer workflows with contextual awareness and guidance. - Work closely with cross-functional teams to translate high-level needs into technical designs and robust implementations. - Contribute to safe AI practices by defining interfaces and logic to prevent and detect unsafe code constructs or misconfigurations. - Collaborate with DevOps and CI/CD engineers to integrate quality feedback loops, instrumentation, and runtime guards into build, deploy, and release pipelines. - Participate in design reviews, code reviews, and retrospectives
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