Senior DevOps Engineer · AI Agent Builder · Bengaluru
7+ years building cloud-native infrastructure and automating CI/CD — cutting deploys from 3–4 days to 2 hours. Now also building autonomous AI agent systems with LangChain, LangGraph & local LLMs.
I'm Anjul — a Senior DevOps Engineer at Oracle, Bengaluru, where I lead automation and infrastructure for core telecom products. My job in one line: make deploys boring. Infrastructure as code, pipelines that catch problems before production does, and observability that surfaces issues before users notice.
I've worked across OCI, Google Cloud, AWS and OpenStack — from migrating 200+ servers to GCP, to running Kubernetes upgrade cycles across live demo environments with zero data loss, to cutting cloud spend by re-architecting where workloads run. I also mentor engineers and push DevOps best practices across teams.
Beyond infrastructure, I build autonomous AI agentic systems — multi-agent architectures with LangChain and LangGraph, RAG pipelines with vector databases, and fully local LLM deployments. My flagship is Brahmaand — a 12-agent autonomous system running entirely on local models at zero cloud cost.
$ whoami → senior devops engineer · ai agent builder · mentor
Sep 2024 — Present
Sep 2022 — Aug 2024
Oct 2020 — Aug 2022
Nov 2018 — Oct 2020
Owned and executed the K8s upgrade cycle (to v1.36) across three live demo environments — planned windows, sequenced rollouts, zero data loss, all apps validated healthy post-upgrade.
Re-architected demo clusters from managed cloud Kubernetes to on-prem kubeadm on OpenStack — eliminating per-node compute, load balancer, storage and egress charges per environment.
Drove cloud security remediation — bastion migration to private subnets, least-privilege access enforcement, and tightened deletion controls protecting critical environment data.
Delivered customer-facing demo environments end to end — auto-scaling and rolling upgrade/rollback use cases, certificate and pipeline coordination, and production-blocking image fixes.
⭐ Flagship AI Project
autonomous multi-agent AI system · Sanskrit for "Universe"
A fully autonomous, containerized multi-agent AI system I designed and built from scratch — 12+ cooperating agents modeled on Hindu cosmology, where each deity's cosmic role maps to its function in the system.
# one message → the right agent acts You (Telegram) │ ▼ [ INDRA ] ─ gateway │ ▼ [ PARAMATMA ] ─ supreme router │ ┌────┼─────────┐ ▼ ▼ ▼ BRAHMA VISHNU SHIVA create preserve destroy │ │ │ ▼ ▼ ▼ agni krishna rudra moon rama nataraja narasimha mahakala │ ▼ result → Telegram ✓
Autonomous multi-agent AI system — 12+ cooperating agents with hierarchical routing, a Redis message bus and a Telegram gateway, all on local LLMs at $0/month cloud cost.
Read the full breakdown ↑Full-stack NIFTY/BankNifty options cockpit + autonomous signal engine — an 11-indicator weighted confluence score drives entries with ATR stop-losses, trailing SLs and auto EOD flatten. In paper-testing before going live.
Private — results after paper-testing wrapsThis very site — hand-coded vanilla HTML/CSS/JS with an immersive WebGL hero, custom domain on Cloudflare DNS, deployed to GitHub Pages by a plain git push.
View source on GitHub →Automation framework for Oracle's core telecom products, built from the ground up — took release deployments from 3–4 days of manual work to 2 hours, with observability wired in via Prometheus, Grafana and Loki.
Proprietary — happy to talk through the designReplaced managed cloud Kubernetes (OKE) with kubeadm clusters on OpenStack for demo environments — same K8s capabilities, zero per-node compute, LB and egress charges, with Longhorn/NFS for storage.
Proprietary — architecture in Highlights aboveHave a project, a role, or just want to talk cloud and Kubernetes? My inbox is always open — I'll get back to you fast.
Say Hello 👋