docs: add plain text resume (copy-paste ready)
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================================================================================
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ROCK LIANG - RESUME
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CONTACT INFORMATION
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Email: [email protected]
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Portfolio: https://riotpiao.com
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GitHub: https://github.com/rockliang
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================================================================================
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PROFESSIONAL SUMMARY
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================================================================================
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Experience:
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6+ years building production-grade infrastructure, backend systems, and LLM
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applications. Specialized in Kubernetes orchestration (Talos Linux, ArgoCD),
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Infrastructure-as-Code (Terraform), distributed systems design, AWS scale
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operations, and GPU-accelerated inference.
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Core Competencies:
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Production Kubernetes (Talos, GitOps/ArgoCD, 99.2% uptime). Terraform IaC
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with drift detection. AWS distributed systems (57+ regions). Golang backend
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services. Observability (Prometheus/Grafana/Loki/Tempo). Message queuing
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(Kafka/Temporal workflows). GPU inference (vLLM, 60% latency improvement).
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Zero-trust networking (OIDC/RBAC).
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Strengths:
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Owning systems end-to-end—design doc through oncall. Building fault-tolerant
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platforms with 99.2% automation. Unblocking teams with clear technical
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communication.
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================================================================================
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EXPERIENCE
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================================================================================
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---
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SELF-HOSTED PRODUCTION (riotpiao.com)
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DevOps / SRE / SDE
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Home Lab | May 2025 — Present
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Challenge & Solution:
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Built AWS from scratch at home on bare-metal Kubernetes—Talos Linux for
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secure immutable OS, ArgoCD for GitOps pipeline automation, SOPS for
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encrypted secrets management, cert-manager for PKI. Result:
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production-grade multi-tenant platform with Kafka, PostgreSQL, S3, GPU LLM
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inference, Temporal workflows in 4-node cluster.
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Tech:
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• Kubernetes (Talos, ArgoCD) — Talos immutable, atomic updates, no SSH, full
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GitOps state. ArgoCD automatic sync with drift detection. Cilium eBPF CNI.
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• Terraform + Kustomize — Declarative infrastructure. State management via
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Terraform Cloud. Kustomize overlays for multi-env.
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• Secrets & Security — SOPS age encryption with git audit trail. Authentik
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OIDC SSO with Kubernetes RBAC. cert-manager + Let's Encrypt (30d renewal,
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7d pre-expiry alerts).
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Infrastructure & Services:
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• Longhorn 3-replica block storage. MinIO S3-compatible API. CloudNativePG
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PostgreSQL with pgvector for embeddings. vLLM GPU inference (Qwen3-32B,
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60% latency vs baseline).
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• Observability stack: Prometheus metrics, Grafana dashboards, Loki logs,
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Tempo traces, OpenTelemetry. 99.2% uptime via monitoring automation.
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• Kafka/Redpanda streaming. Temporal workflows for fault-tolerant jobs.
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Forgejo CI/CD with Docker registry. DinD runners for parallel builds.
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---
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ROYAL BANK OF CANADA (RBC)
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Lead Software Engineer
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Toronto, ON | Nov 2024 — May 2026
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Challenge & Solution:
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Deployments were manual and slow—teams blocked 2+ hours per release waiting
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for provisioning. Standardized on Terraform Cloud for idempotent IaC. Built
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Temporal workflows for multi-cloud orchestration with built-in retry logic
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and idempotency keys. Reduced deploy time from 2 hours to 20 minutes,
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achieved 99.2% automation.
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Drift Detection & Reconciliation:
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• Built Kubernetes CronJob (Golang) to continuously detect and reconcile
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Terraform state drift against actual infrastructure. Automatically
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detects divergence (network policies, security groups, storage) and
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triggers remediation without manual intervention.
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• Coordinated across 4 platform teams, unified 200+ microservices into
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single IaC standard. Cut onboarding time for 12 teams.
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Notifications & SLA:
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• Designed Slack notification service with Golang workers. Alerts on apply
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failures, drift detection, provisioning bottlenecks. Operators resolve
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issues in <5 minutes via notification-driven workflow.
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Stakeholder Alignment:
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• Led requirement gathering across 4 platform teams. Translated technical
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decisions for non-technical stakeholders. Secured buy-in for platform
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migration. Unblocked 3 stalled projects by disambiguating specs.
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Tech:
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• Golang, Kubernetes, Terraform Cloud, IaC, Distributed Systems
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• Slack API, multi-cloud orchestration, state drift reconciliation
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• Notification-driven operators, 99.2% automation
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---
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AMAZON WEB SERVICES (AWS)
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Senior Software Engineer (Step Functions)
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Seattle, WA | 2022 — 2024
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Challenge & Solution:
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Owned Distributed-Map from design doc to production launch across 57+
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regions. Under tight deadline, introduced separate state in Map vs new
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functions—simplified customer adoption. Built checkpoint recovery for
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mid-workflow failures so customers resume without full re-run.
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Distributed Systems Engineering:
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• Solved critical edge cases: race conditions in concurrent state updates,
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dependent service failures, message deduplication, exactly-once semantics
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across distributed workers.
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• Introduced JSON state input for larger payloads—unlocked new customer use
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cases (batch processing, ML model serving, data pipelines).
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Production Ownership & Reliability:
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• Full oncall ownership—built CloudWatch dashboards, wrote operational
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runbooks, debugged production issues live. Achieved sub-100ms P99 latency
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across 57+ regions and 20x burst traffic scaling.
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• Disaster recovery procedures and incident response. State management for
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failed/retried jobs.
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Tech:
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• Java, AWS Step Functions, DynamoDB state storage, gRPC, Distributed Systems
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• CloudWatch observability, ownership, disaster recovery, exactly-once delivery
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• 57+ regions, sub-100ms P99, 20x burst traffic
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---
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NETFLIX TITUS (Container Orchestration)
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Software Engineer Intern
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Los Gatos, CA | May — Aug 2019
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Challenge & Solution:
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Streamlined Personal Data Detection (PDD) to identify classified data
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exfiltration anomalies—achieved 97.8% accuracy with minimal false positives.
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Built fault-tolerant Golang connector for PDD integration with 28% p99
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latency improvement over legacy implementation.
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Compilation & Integration:
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• Re-integrated SmartRegex with CMake & C++ on Linux/Unix platforms.
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Achieved 5x faster deployment through automated build pipeline and
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dependency resolution.
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• Prevented classified data leakage across Netflix's distributed workload
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platform.
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Tech:
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• C++, CMake, Golang, Docker, pattern matching, fault tolerance
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• Build automation, 97.8% detection accuracy, 28% latency improvement
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---
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NAV CANADA (Air Traffic Control Systems)
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Summer Student
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Ottawa, ON | May — Aug 2018
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Challenge & Solution:
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Maintained enterprise CFPS web application in Agile development. Built
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Django NOTAMJ polls app to meet iteration goals. Improved deploy stability
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with Sonar code coverage analysis—reduced defect escape rate.
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Frontend & User Experience:
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• Created FWGS weather briefing interface with ReactJS for Air Traffic
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Control. Real-time meteorological data visualization for pilot briefings.
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• Deployed to Canadian airspace (50+ airports). Improved ATC
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decision-making with cleaner weather briefing UX.
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Tech:
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• ReactJS, Django, Agile methodology, Sonar code coverage
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• Weather data visualization, pilot decision support systems
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================================================================================
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TECHNICAL SKILLS
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================================================================================
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Languages:
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Golang, Java, Python, C++, JavaScript/TypeScript, SQL, Bash
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Cloud & Infrastructure:
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Kubernetes (Talos Linux, k3s, ArgoCD GitOps)
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Terraform (IaC, state management, drift detection)
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Docker, OpenShift, AWS (DynamoDB, Step Functions, CloudWatch)
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Distributed Systems:
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Temporal workflows, Kafka/Redpanda streaming
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gRPC, message queuing, exactly-once semantics
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State management, disaster recovery, idempotency
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LLM & AI:
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vLLM (GPU inference, Qwen3-32B, 60% latency improvement)
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KServe orchestration, Ollama, TEI embeddings
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Vector databases (pgvector), model serving
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Observability & Monitoring:
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Prometheus (metrics), Grafana (dashboards)
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Loki (log aggregation), Tempo (distributed tracing)
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OpenTelemetry, CloudWatch, alerting & runbooks
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Networking & Security:
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Authentik OIDC SSO, Kubernetes RBAC
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cert-manager TLS, SOPS encryption
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Cloudflare Tunnel (zero-trust), network policies
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PKI, service-to-service auth
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Data & Storage:
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PostgreSQL (CloudNativePG, pgvector)
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DynamoDB, MinIO S3, Longhorn block storage
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Data modeling, exactly-once consumption
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CI/CD & DevOps:
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Forgejo Actions, GitHub Actions
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Docker container registry, Kustomize
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GitOps, declarative infrastructure
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================================================================================
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EDUCATION
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================================================================================
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University of Ottawa, Ottawa, Ontario
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Master of Science in Computer Science (Software Systems)
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2020 — 2021
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University of Ottawa, Ottawa, Ontario
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Bachelor of Science in Computer Science (Honours)
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2016 — 2020
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================================================================================
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