~/career/ — chitender@platform-eng — zsh — 132×40 ⎈ ● k8s-prod-2026
Senior Cloud Architect · Platform & SRE Engineering
#kubernetes#sre#ebpf#finops#ai-ops#observability
email : chitenderkumar.16@gmail.com
phone : +91 8130 089 176
linkedin : linkedin.com/in/chitenderkumar
location : Delhi, India · open to remote
cert : CKA / CNCF
seeking : Staff / Principal / SRE ManagerSenior Cloud Architect and SRE leader with 10+ years delivering production-grade Kubernetes platforms on AWS EKS and Azure AKS at scale. Specializes in reliability engineering (SLO/SLI/error budgets), cost-optimized compute, and automation-first operations.
Track record of shipping internal platforms — including an AI-assisted incident response system (Aria/InfraInsights), eBPF-based CNI migration (Cilium), and Karpenter-driven FinOps programs — that measurably reduce MTTR, alert noise, and operational toil.
| Metric | Value | Context |
|---|---|---|
| 🕐 Years in production | 10+ | Platform & SRE |
| ⚡ RCA surface time | < 2 min | Aria AI assistant |
| 📉 Alert noise reduction | −30% | Over 18 months |
| 🧠 Incident pairs trained | 45K | RAG corpus |
▸ Senior Cloud Architect @ Innovaccer · Jul 2024 — Present
Lead platform engineering & SRE for a healthcare data activation platform running thousands of Kubernetes workloads across EKS and AKS.
| Domain | Project | Impact |
|---|---|---|
[networking] |
Cilium CNI migration on EKS/AKS — Led end-to-end migration from legacy CNI to Cilium (eBPF). Enforced L4/L7 policy, improved network observability, reduced connection-level latency | Zero production outages during cutover |
[finops] |
Karpenter program at scale — Spot/On-Demand mix, instance diversity, disruption windows. Right-sized node pools via load testing | Cut compute cost while holding P99 within SLO during peak |
[ai-ops] |
Aria — AI-assisted incident response — LLM-powered RCA assistant (Gemma 4 + Qdrant + Ollama on AKS), trained on ~45K historical incident Q&A pairs | Surfaces root causes in < 2 min inside on-call workflows |
[governance] |
Multi-account lifecycle tooling — Python + Kubernetes API tooling for cross-account operations using AWS STS | Reduced manual provisioning overhead; enforced security guardrails at scale |
▸ Lead SRE → SRE Manager → Staff SRE @ Innovaccer · Feb 2021 — Sep 2024
Built and led the SRE function from IC to team lead. Owned availability, incident command, and measurable reliability improvements across critical services.
| Domain | Project | Impact |
|---|---|---|
[observability] |
InfraInsights platform — Full-stack observability + AI-RCA platform (Prometheus / Grafana / OTel / CloudWatch) with SLO dashboards, burn-rate alerts, and auto-linked playbooks | Replaced fragmented monitoring with a single pane of glass |
[controllers] |
KubeNightwatch operator — Production K8s controller enforcing time-window and change-freeze policies; Slack + Jira integration; deletes out-of-policy resources | Eliminated an entire class of unauthorized change incidents |
[data] |
Kafka & OpenSearch reliability — ISR instability, partition skew, GC-related consumer lag via tuning, scaling patterns, and codified runbooks | Significant drop in repeat Kafka incident volume |
[chaos] |
Chaos engineering practice — Spot interruption drills and failover chaos tests | Exposed hidden single points of failure before they became incidents |
[platform] |
Postmortem culture — Drove postmortems to time-bound, code-level fixes | Reduced noisy pages > 30% over 18 months; materially improved MTTR |
| Company | Role | Period |
|---|---|---|
| Atlan | SDE II — Platform Engineering | Feb 2020 — Jan 2021 |
| Delhivery | Senior DevOps Engineer | Jun 2019 — Feb 2020 |
| Innovaccer | Infrastructure Engineer | Aug 2017 — Jul 2019 |
| Telenity | Solution Architect / Engineer Operations | Feb 2015 — Aug 2017 |
|
LLM-powered RCA system (Gemma 4 + Qdrant + Ollama on AKS), trained on ~45K Q&A pairs from historical incidents. Surfaces root-cause hypotheses in < 2 min, integrated into on-call tooling.
|
Prometheus / Grafana / OTel / CloudWatch unified observability with SLO dashboards, burn-rate alerts, and auto-linked runbooks. Replaced fragmented monitoring across multi-tenant EKS/AKS.
|
|
Kubernetes operator enforcing time-window and change-freeze policies; deletes out-of-policy resources; Slack/Jira integration. Eliminated unauthorized change incidents entirely.
|
Workload-aware Spot/On-Demand autoscaling with instance diversity, disruption windows, and forecast-based pre-warm for batch workloads. Cut compute cost while sustaining P99 SLOs.
|
KUBERNETES_CLOUD = "EKS, AKS, GKE, Karpenter, Cilium (eBPF), Helm, Argo CD, Flux, Operators, KEDA"
CLOUD_PLATFORMS = "AWS (EKS, STS, EC2, RDS, S3, CloudWatch, IAM), Azure (AKS, Monitor), GCP"
OBSERVABILITY = "Prometheus, Grafana, OpenTelemetry, Alertmanager, CloudWatch, Jaeger, Loki"
IAC_AUTOMATION = "Terraform, Ansible, Python, Go, Bash, Jenkins, GitLab CI, GitHub Actions"
DATA_MESSAGING = "Kafka, OpenSearch / Elasticsearch, Redis, PostgreSQL, Qdrant (vector DB)"
AI_ML_OPS = "LLM integration (Gemma 4, Ollama), RAG pipelines, vector embedding, AI-assisted RCA"
RELIABILITY = "SLO/SLI/Error Budgets, Incident Command, Chaos Engineering, DORA Metrics, Postmortems"✓ Certified Kubernetes Administrator (CKA) — CNCF
✓ B.Tech, Computer Science — LDIET, 2016
* feat(ai-ops): Aria v2 — multi-cluster incident correlation
* feat(finops): Karpenter forecast-based pre-warm for batch windows
* feat(ebpf): Cilium Hubble flows → OTel pipeline
* chore(platform): Multi-tenant control/data plane IaC standardization
K8S · EBPF · OTEL · KARPENTER · KAFKA · TERRAFORM · GO · PYTHON · LLM-OPS
chitender@platform:~ $ exit 0 # thanks for reading — ck / 2026
