~/career/ — chitender@platform-eng — zsh — 132×40 ⎈ ● k8s-prod-2026
Senior Cloud Architect · Platform & SRE Engineering
#kubernetes#sre#ebpf#finops#ai-ops#observability#multi-tenancy#healthcare-infra
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 (including Azure Government) at scale, in a HIPAA-regulated healthcare environment. Specializes in reliability engineering (SLO/SLI/error budgets), multi-tenant platform architecture, secure networking, and automation-first operations.
Track record of shipping internal platforms — an AI-assisted incident response system (Aria/InfraInsights), eBPF-based CNI migration (Cilium), a centralized LLM egress layer, PHI-safe multi-tenant telemetry architecture, and Karpenter-driven FinOps programs — that measurably reduce MTTR, alert noise, cost, 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 |
| 🚀 Egress throughput gain | +37% | TCP passthrough vs HTTP mode (735 vs 534 RPS) |
| 🌐 NAT IP whitelist entries eliminated | per-env → 1 | Centralized egress architecture |
▸ Senior Cloud Architect @ Innovaccer · Jul 2024 — Present
Lead platform engineering & SRE for a multi-tenant healthcare data activation platform running thousands of Kubernetes workloads across EKS, AKS, and Azure Government.
| Domain | Project | Impact |
|---|---|---|
[networking] |
Centralized LLM egress layer (HAProxy) — Designed single-egress architecture in an Azure hub VNet: all customer VNets peered in, IPSec S2S VPN to an AWS-hosted LLM inference platform. Benchmarked TCP passthrough vs HTTP mode under load; pinned upstream IPs with round-robin; tuned LLM-appropriate timeouts (tunnel 3600s for streaming) |
Eliminated per-environment NAT Gateway IP whitelisting; +37% throughput (735 vs 534 RPS); zero-downtime cutover |
[observability] |
Multi-tenant telemetry architecture — Shared OTEL Collector design with tenant.id propagation via W3C Baggage, cardinality-safe metric labeling, and shared ClickHouse tables with tenant-leading ORDER BY + row-level security policies |
Single collector fleet serving all tenants with hard tenant isolation and query locality |
[security] |
PHI-safe tracing for GenAI workloads — Identified sensitive data flowing through LLM trace span attributes (prompts, tool I/O, agent outputs); drove forensic scoping via ClickHouse queries, designed collector-level redaction, attribute allowlisting, retention purge, and data-plane isolation for AI services | Closed a compliance-critical telemetry exposure class; redaction now enforced at pipeline level, not app discretion |
[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 |
[interop] |
HL7 MLLP clinical connectivity — AKS ↔ hospital interface-engine (Epic) integration: internal NLB in IP-target mode for long-lived MLLP TCP sessions, AWS Site-to-Site VPNs with hardened tunnels (IKEv2, AES-256, SHA-256, DH14) against customer Palo Alto firewalls, Azure Network Watcher–driven connectivity forensics | Production clinical data exchange with deterministic failover; runbook-codified diagnostics |
[platform] |
Single-tenant network conversion — Collapsed a two-VNet multi-tenant control/data-plane topology into a single-VNet dedicated AKS deployment for a strategic enterprise healthcare customer | Simplified routing/peering surface; faster deployment path for dedicated tenants |
[security] |
Elastic (ECK) hardening — Root-cause'd silently-ignored Helm securityContext values; enforced non-root Elasticsearch (runAsNonRoot, seccomp RuntimeDefault, capabilities.drop: ALL) at the nodeSet level |
Cleared container-runs-as-root findings across the search tier without data-dir permission regressions |
[governance] |
Container vulnerability SLA program — Authored remediation contract for customer-facing workloads: Critical 15d / High 30d / Medium 90d / Low 180d, wired into CI and registry scanning | Contractual, auditable patching cadence for regulated customers |
[gitops] |
Multi-cloud GitOps strategy — Per-cloud Helm chart separation with branch-isolation model for GCP/Azure/AWS deployment tracks | Prevented cross-cloud config bleed; defensible promotion model |
[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 |
[data] |
Lakehouse operations — Databricks Unity Catalog external location lifecycle, Delta Share provisioning, metastore governance for healthcare data workloads | Self-service, permission-scoped data access without infra tickets |
[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.
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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.
|
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Redaction-at-collector pipeline for GenAI trace data: attribute allowlisting, tenant-isolated ClickHouse storage (row policies + tenant-leading sort keys), retention purge strategy. Made "no PHI in observability" an enforced platform invariant.
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Single HAProxy egress in a hub VNet, all env VNets peered in, IPSec S2S to AWS inference platform. TCP passthrough with pinned upstreams beat HTTP mode by 37% under load. One IP to whitelist instead of one per environment.
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KUBERNETES_CLOUD = "EKS, AKS, GKE, Karpenter, Cilium (eBPF), Helm, Argo CD, Flux, Operators, KEDA, ECK"
CLOUD_PLATFORMS = "AWS (EKS, STS, VPN, EC2, RDS, S3, MSK, IAM), Azure + Azure Government (AKS, VNet, Network Watcher, PostgreSQL Flexible Server), GCP"
OBSERVABILITY = "Prometheus, Grafana, OpenTelemetry (Collector, W3C Baggage), ClickHouse, Alertmanager, CloudWatch, Jaeger, Loki"
NETWORKING = "HAProxy, IPSec S2S VPN (IKEv2), VNet peering, NLB (IP-target), HL7 MLLP, NSG forensics, Cloudflare"
IAC_AUTOMATION = "Terraform, Ansible, Python, Go, Bash, Jenkins, GitLab CI, GitHub Actions, GitOps"
DATA_MESSAGING = "Kafka/MSK, OpenSearch / Elasticsearch, Redis, PostgreSQL, ClickHouse, Databricks (Unity Catalog, Delta Share), Qdrant"
AI_ML_OPS = "LLM integration (Gemma 4, Ollama), RAG pipelines, LLM egress/inference networking, GenAI trace redaction, AI-assisted RCA"
RELIABILITY = "SLO/SLI/Error Budgets, Incident Command, Chaos Engineering, DORA Metrics, Postmortems, Vulnerability SLA programs"
COMPLIANCE = "HIPAA-regulated infra, PHI data-flow controls, tenant isolation, audit-ready remediation SLAs"✓ Certified Kubernetes Administrator (CKA) — CNCF
✓ B.Tech, Computer Science — LDIET, 2016
* feat(security): PHI-safe OTEL pipeline — collector redaction + tenant-isolated ClickHouse
* feat(networking): centralized HAProxy LLM egress — TCP passthrough, IPSec to AWS inference
* 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