SRE Monitoring Platform Software Engineer (Entry Level)
Bitdeer
Bitdeer is a world-leading technology company for AI and Bitcoin mining infrastructure.
Bitdeer is committed to providing comprehensive Bitcoin mining solutions for its customers and building AI computational infrastructure to support the AI revolution. Bitdeer handles complex processes involved in computing such as equipment procurement, transport logistics, data center design and construction, equipment management, and daily operations. Bitdeer also offers advanced cloud capabilities to customers with high demand for artificial intelligence.
Headquartered in Singapore, Bitdeer has deployed data centers across multiple countries, including the United States, Norway, Bhutan, and Ethiopia.
To learn more, visit [ Position OverviewBitdeer is building an AI-operated GPU cloud — a global fleet of self-built and OEM-rented data centers running the world's most valuable compute, run by a platform that observes, protects, and operates the fleet. The SRE Platform team builds the monitoring and automation substrate that every other squad — storage, network, GPU, K8S, and L1 operators — depends on. Their signals become the system you help build.
As an entry-level Software Engineer on the SRE / Monitoring Platform team, you contribute to the NeoCloud SRE platform — the multi-region system that observes, protects, and operates a GPU rental fleet across self-built and OEM-rented data centers. You join a bounded context led by a senior engineer, take well-scoped components from design to production code that ships through GitOps + the CICD release pipeline, follows the Plugin Framework conventions, meets declared SLOs, and stays drift-free.
This is a build + learn role. You write code, write tests, and operate what you build under the guidance of a senior engineer. You participate in on-call as a shadow before taking primary. Within 12 months, you should be delivering components independently within your assigned area and growing toward owning a sub-context.
Key Responsibilities Where you'll contribute (guided by a senior engineer)
- Collection + Storage — help build collection-agent, metrics-store / logs-store / traces-store / profiles-store, enrichment-service, collection-monitor. Write ingestion, query, and storage-path code.
- Alert + Correlation + SLO — contribute to alert-engine-framework, alert-correlation, slo-framework; implement and tune default alert rules.
- Topology + Cluster-Health — contribute to topology-service, cluster-health-rollup, OSS-SRE-tool collection plugins for K8s / Slurm / Ray / Volcano / Kueue / KubeRay.
- Remediation + Workflow + Jobs — help build remediation-actuator, orchestration / workflow components, inspection probes, job-scheduler.
- Observability instrumentation — instrument services with metrics, logs, and traces via OpenTelemetry; build dashboards; write runbooks an on-call can follow.
- Test discipline — write unit / integration / contract tests for everything you ship; participate in chaos and soak tests led by senior engineers.
- Greenfield with a well-defined vision. The Plugin Framework, GitOps pipeline, and SLO framework are decided; you build components inside them with a clear blueprint — not from a blank page.
- You learn the full observability stack at production scale — ingest, query, storage — by building it, not just using it.
- Mentorship-heavy. You work directly with senior and principal engineers who own the architecture; their expertise becomes your growth path.
- 0-2 years of software engineering experience (new graduates with strong projects or internships welcome).
- Solid fundamentals in one programming language — Go (preferred), Python, Java, or Rust. You can write clean, tested, readable code and explain your design choices.
- CS fundamentals — data structures, algorithms, concurrency, basic networking (TCP / and operating-system concepts (processes, threads, I/O). You can reason about correctness and performance.
- Distributed systems basics — you understand the ideas behind idempotency, retries, back-pressure, caching, and eventual consistency, even if you haven't operated them at scale yet. Eagerness to go deep.
- Monitoring / observability exposure — some hands-on with Prometheus, Grafana, Loki, or similar; can write a basic PromQL query and instrument a service. Eagerness to learn the ingest, query, and storage path of a real observability stack.
- Familiarity with Linux and the shell; comfort reading system logs and using standard debugging tools.
- Kubernetes basics — understand Pods, Services, Deployments; have run something on K8s (a project, lab, or internship).
- Git + CI basics — branching, pull requests, and have used a CI pipeline (GitHub Actions, GitLab CI, or similar).
- Test discipline — you write unit and integration tests as a habit, not an afterthought.
- Communication — clear written and verbal English; can write a good PR description and ask good questions.
- Curiosity and a learning mindset — the most important qualifier. You're excited to learn GPU / AI infrastructure, AIOps, distributed systems, and observability at production scale.
- Internship or project in monitoring / observability, telemetry pipelines, or platform / SRE tooling.
- Exposure to GPU / AI-infra — DCGM, InfiniBand / RoCE, Kubernetes GPU Operator, Slurm / Ray. Interest counts more than depth.
- Exposure to AIOps / ML-adjacent tooling (anomaly detection, alert correlation).
- Contributions to open-source observability or cloud-native projects.
$101k - $161k
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