We are looking for a Principal Engineer to lead the architectural vision of the platforms core. In this role, you will be the internal technical authority responsible for building a unified, high-performance engine that processes massive telemetry streams and runs advanced predictive models, regardless of where the infrastructure resides.
What youll be doing:
Unified Architectural Vision: Lead the design of a flexible, high-scale architecture that supports both multi-tenant SaaS environments and complex on-premises deployments.
Operationalizing Predictive Models: Bridge the gap between AI research and production by architecting the framework that runs sophisticated predictive algorithms at scale, ensuring they are robust enough for mission-critical environments.
High-Scale Engineering: Design distributed systems to handle the extreme telemetry density of large-scale AI clusters, ensuring efficient data ingestion, processing, and real-time analysis.
Cross-Organizational Leadership: Collaborate with networking and infrastructure teams to define the technical standards that enable the AIOps platform to integrate seamlessly with global AI infrastructure.
Technical Excellence: Drive the engineering roadmap, mentor senior staff, and serve as the final authority on architectural decisions, ensuring the platform meets the highest standards of reliability and scalability.
Requirements: What we need to see:
Education: B.Sc./M.Sc. in Computer Science, Computer Engineering, or a related technical field.
Experience: 12+ years of experience in software engineering, with a proven track record of architecting complex, high-scale products delivered via SaaS and/or on-premises enterprise models.
Architectural Sovereignty: Deep expertise in building environment-agnostic distributed systems, using technologies like Kubernetes to ensure portability across cloud and private data centers.
Core Systems Programming: Expert-level proficiency in languages such as Go, C++, or Rust, with a focus on high-performance, concurrent architectures.
Data Infrastructure: Extensive experience with high-throughput data processing (e.g., Apache Kafka) and managing large-scale telemetry or time-series data.
Ways to stand out from the crowd:
The "0 to 1" Mindset: A proven track record of taking a complex architectural concept from a whiteboard to a stabilized, production-grade platform.
A "Systems" Thinker: You don't just write software; you understand the full stack, from how data moves across the wire to how its processed in a distributed cluster.
Infrastructure Evangelist: Experience in leading large-scale technical migrations or introducing modern engineering paradigms (like Cloud-Native or GitOps) into complex, high-stakes environments.
Practical Innovation: The ability to simplify complex problems and build internal tools or frameworks that empower other engineering teams to move faster.
This position is open to all candidates.