Are you a seasoned AI Engineer with a passion for building robust, scalable, and intelligent systems? Do you thrive in a collaborative environment where innovation is encouraged and your contributions directly impact a widely used observability platform? If so, we want you to join our Grafana Ops team!
As a Senior AI Engineer, you will play a pivotal role in designing, developing, and deploying cutting-edge AI/ML solutions that enhance the capabilities of Grafana Ops. You’ll work with a talented group of engineers, product managers, and SREs to tackle complex challenges in anomaly detection, root cause analysis, and predictive insights, ultimately helping our users gain deeper visibility and control over their systems.
This is a unique opportunity to contribute to a high-impact product within a fast-growing company, leveraging your expertise to build the future of observability.
What you’ll do:
- Design, develop, and deploy AI/ML-driven features and enhancements within the Grafana Ops platform.
- Collaborate with cross-functional teams (Product, Engineering, SRE) to define requirements, design solutions, and deliver high-quality products.
- Build and maintain robust data pipelines and ML infrastructure to support real-time data processing and model training.
- Implement and optimize machine learning algorithms and models for anomaly detection, root cause analysis, and predictive insights.
- Contribute to the entire software development lifecycle, including testing, deployment, monitoring, and maintenance of AI/ML services.
- Stay up-to-date with the latest advancements in AI/ML, distributed systems, and observability, and evangelize best practices within the team.
What you’ll bring:
- 5+ years of experience as an AI/ML Engineer, Data Scientist, or Backend Engineer with a strong focus on machine learning applications.
- Strong proficiency in programming languages such as Go, Python, or Java. Experience with Go is a significant plus.
- Demonstrable experience with distributed systems and cloud platforms (AWS, GCP, Azure).
- Solid understanding of machine learning principles, algorithms, and MLOps practices.
- Experience with containerization technologies (Docker, Kubernetes) and CI/CD pipelines.
- Familiarity with observability tools (Prometheus, Grafana, Loki, Tempo) is a strong advantage.
- Excellent problem-solving skills, attention to detail, and ability to work independently and as part of a team.
- Strong communication and interpersonal skills, with the ability to articulate complex technical concepts to diverse audiences.
- Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
We encourage you to apply, even if you don’t meet every single requirement.
