Job Url: https://job-boards.greenhouse.io/cavnue/jobs/5536254004

Job Description: Core Responsibilities:

Expert in real time stream processing using C++, Python or Go
Drive production of high-quality code through standards adoption, lifecycle testing, and continuous monitoring for opportunities to improve.
Engineer data structures, databases, and processing pipelines for optimal performance and reactivity in a production environment.
Develop and maintain APIs and integration patterns to support the deployment, orchestration, and operation of AI agents and multi-agent systems.
Implement comprehensive monitoring, logging, and alerting for platform health, data quality, and algorithm performance.
Collaborate closely with hardware engineers, software developers, and researchers on sensor selection, system architecture, calibration procedures, and resolving integration challenges.
Maintain clear documentation for algorithms, system designs, integration points, and operational procedures.
Assurance of high-quality code through standards adoption, lifecycle testing, and continuous monitoring for opportunities to improve
Establish low-latency/high throughput APIs on streaming packets of data from the cloud and edge
Contribute to a health and positive engineering culture
Nice to Have Responsibilities:

Work in a number of languages (Python, C++, Go), using established libraries and technologies (Redis, BigQuery, Pulsar, Flink) in a cloud native Kubernetes environment  
Design, build, manage, and optimize scalable, secure, and cost-effective infrastructure and platforms specifically tailored for AI/ML workloads on cloud platforms
Support the frameworks that enable fine-tuning, serving, and monitoring Large Language Models (LLMs) efficiently and reliably.
Build and manage scalable data ingestion, storage (e.g., data lakes), and processing pipelines optimized for real time performance and fast historic query performance
Stay current with the latest advancements and best practices in AI/ML, MLOps, LLMs, and agent technologies, driving continuous improvement. The rapid evolution of this field necessitates constant learning and adaptation.
Requirements:

5+ years of professional experience in software engineering, platform engineering, or integration engineering.
Bachelors Degree in Computer Science, Engineering or equivalent experience 
Proficiency in programming languages commonly used for both platform development and algorithm implementation, such as Python and C++
Experience with cloud platforms (AWS, Azure, or GCP) and core infrastructure services
Experience with containerization (Docker) and orchestration (Kubernetes).
Excellent problem-solving, analytical, and troubleshooting skills
Strong communication and collaboration skills
Experience working with Git, GitHub, Jira, Confluence – or similar tools – including complex operations and workflows
Comfortable working in a Linux development environment 
History of building software in highly-collaborative environments
Willingness and eagerness to think about how to solve problems for multiple users through common interaction patterns
Experience designing practical and compelling architectures and systems
You demonstrate curiosity and initiative to understand complex systems, with the ability to make meaningful progress independently and with minimal guidance.