LIVE · Cohorts running ·

Full Stack Cloud &
AIOps Engineering,
Built for Builders.

A 6–8 month live program co-built with India's premier institutes — designed so you ship self-healing infrastructure, deploy AI at scale, and graduate with proof of work hiring teams actually care about.

1,400+ engineers applied to the last cohort
across India · UAE · Singapore

In partnership with
TIH at IIT Bombay TIH at IIT Bombay
Upcoming cohorts

Choose your cohort.

Same curriculum, same mentors — three regional cohorts so the live sessions land in your evening, not your 3 AM.

Jul15
India

Cohort 04 · 8:00 PM IST

Next cohort · Live online · Tue & Sat
Jul22
UAE

Cohort 04 · 7:30 PM GST

Next cohort · Live online · Tue & Sat
Jul29
Singapore

Cohort 04 · 9:00 PM SGT

Next cohort · Live online · Wed & Sun
The AI Shift

Traditional DevOps
is evolving. Are you?

The world has moved beyond "keeping the lights on." In the AI-first world, infrastructure must be intelligent, autonomous, and self-healing. This program retools you for that reality.

01 · Automation

From Manual Scripts to Agentic Workflows

Don't just automate — build agents that manage your cloud, ship infra-code, and respond to incidents end-to-end without a human waking up at 3 AM.

02 · Observability

From Monitoring to Observability

Predict failures with AI before they happen. Build distributed tracing, anomaly detection, and SLO-driven runbooks that catch the unknowns, not just the dashboards you remembered to set up.

03 · LLM-Ops

From Standard Apps to LLM-Ops

Deploy and scale Large Language Models with the same rigor as microservices — model serving, GPU autoscaling, eval pipelines, and cost guards baked in.

Industry Signal

The demand for this
role is exploding.

Every major analyst and tier-1 publication is calling out the AIOps role spectrum — AIOps, MLOps, Forward Deployed, and Cloud Architects — as the highest-leverage technical roles of the decade. Here's what they're saying.

"AIOps is now mainstream — and the talent shortage is acute"

By 2026, 60% of large enterprises will run AIOps-augmented operations, with anomaly detection and self-healing infrastructure becoming table-stakes for production systems.

Gartner

"MLOps is the missing link between AI prototypes and real product impact"

Companies that institutionalise MLOps — feature stores, eval pipelines, model rollback — ship AI features 5× faster and see meaningfully better adoption than teams shipping notebooks to prod.

McKinsey Digital

"The new hot job in AI: forward-deployed engineers"

Job postings for forward-deployed engineers have increased by more than 800% in 2025 as enterprises race to embed AI inside core business workflows.

Financial Times

"Cloud architects are the unsung backbone of the AI era"

As inference workloads scale, the next decade belongs to architects who can design multi-region GPU clusters, optimise for cost-per-token, and keep latency in check across edge and cloud.

Harvard Business Review
Roles That Define the Next Decade

Prepare for the most
future-proof roles in tech.

Four roles that hiring teams are racing to fill — at FAANG, scaling startups, and AI-first enterprises across India, UAE, and Singapore.

AIOps Engineer

Use machine learning to enhance and automate IT operations — anomaly detection, predictive scaling, self-healing systems.

MLOps Engineer

Bridge the gap between data science and production — feature stores, model serving, eval pipelines, and CI/CD for ML.

Forward Deployed Engineer

Embed with customers to design and ship complex AI solutions directly inside their business workflows — the highest-leverage AI role today.

Cloud Architect (AI)

Design high-performance GPU clusters and inference platforms for the next generation of software — multi-region, multi-tenant, AI-first.

The Method

Understand how an AIOps
engineer's work cycle operates.

Bridging business needs and AI execution
1

Understand the Business Reality

Start by understanding the operational pain — what the business actually spends on, not just the stated requirement.

2

Define the Right Problem

Translate business pain into a clear, solvable problem worth using AI for — sized, scoped, and measurable.

3

Design the AI Approach

Decide what AI should do — what data it will use, how success will be measured, and where the system can fail safely.

4

Build Within Real Constraints

Develop solutions that fit existing data, systems, security, and infrastructure — not in a lab, but inside production.

5

Deploy into Production

Ship working AI into live environments where real users depend on it. Real on-call. Real rollback paths.

6

Own Outcomes and Improve

Monitor performance, fix failures, and continuously improve the system based on real usage — not vanity metrics.

Alumni Stories

Production AI shipped.
Career moves real.

Alumni are running AIOps platforms at Razorpay, LinkedIn, and CRED, shipping LLM infra in Dubai and Singapore, and pulling 50–90% comp jumps moving from traditional DevOps into AI-native roles.

🇮🇳 Indian alumni
Karthik — Razorpay, India "Shipped a self-healing K8s controller in week 16. Promoted to Staff."
UAE · NRI
Vikram — Careem, Dubai "Moved from SRE to Lead MLOps Engineer with a 78% comp jump."
🇸🇬 Singapore
Rahul — GovTech, Singapore "Got the FDE offer 7 weeks before graduation. SGD 180K + GPU budget."
+78% SRE → MLOps Lead Vikram Rao SRE, Careem → Lead MLOps, Careem
+62% Promoted to Staff Karthik Iyer Senior DevOps → Staff AIOps, Razorpay
+95% Cloud → AI Infra Rahul Sharma Cloud Engineer → FDE, GovTech SG
+54% Switched stack Meera Pillai Backend Eng → AIOps Lead, CRED
Backed by Top Academia

The TIH at IIT Bombay
Advantage.

Co-built with the TIH Foundation for IoT & IoE at IIT Bombay — institute-backed curriculum and recognised credentials grounded in research from one of India's premier engineering institutes.

TIH at IIT Bombay interior campus
Faculty & Advisors
  • Prof. Sameer Joshi Principal Investigator
  • Prof. Anjali Deshmukh Co-Chair · AIOps
  • Prof. Rohan Iyer Faculty · Cloud Systems
  • Prof. Sanjay Kulkarni Mentor · Production AI
Your Credential

The Certificate You
Walk Away With.

A verifiable credential co-issued by the TIH Foundation for IoT & IoE at IIT Bombay and the Edzor Centre of AI & Technological Excellence — recognised across our 220+ hiring partners.

  • Institute-backed credential co-issued with TIH at IIT Bombay
  • Verifiable certificate ID — recognised across 220+ hiring partners
  • CKA/CKAD-aligned curriculum — sit those exams after
  • Valid across India · UAE · Singapore cohorts
Sample TIH at IIT Bombay × EdWagon certificate
Invest in your future

One program.
Three local cohorts.

Pricing set locally so the program stays accessible across markets — financing options available in every region.

Only 8 seats left for the June cohort — close in 9 days
₹75,000

Incl. GST · Includes labs, cloud credits, capstone & placement support

No-cost EMI starts at ₹4,500/mo via partner lenders. Counsellor will walk you through lender terms on the fit call.

Program Includes
  • All Theory + Lab sessions
  • $200 in real cloud credits
  • 1:1 weekly mentorship
  • 4 production-grade projects
  • CKA/CKAD-aligned curriculum
  • Lifetime alumni access
  • Weekend industry masterclasses
  • Mock interviews + resume review
  • Lifetime access to recordings
  • Joint TIH at IIT Bombay × EdWagon certificate
    • Mastering the "engine room" of the cloud — kernel architecture, scheduling, signals.
    • Process & memory management, advanced networking (TCP/IP), system security hardening.
    • AI integration: use LLMs to analyze system logs and debug kernel panics.
    Linux strace tcpdump bpftrace
    • Automation-first mindset: Python for DevOps, Bash deep-dive, error-resilient scripts.
    • Git Flow, GitHooks for automated testing, signed commits, secret scanning.
    • Designing pipelines that scale across teams and repos.
    Python Bash GitHub GitLab
    • VPC networking, IAM least-privilege security, AZ + region design.
    • Serverless (Lambda), event-driven architectures, multi-region high availability.
    • Cost optimization patterns for production workloads.
    AWS EC2 S3 Lambda CloudWatch
    • Disposable, replicable systems — Terraform language deep-dive, modules, state management at scale.
    • Ansible for configuration management, idempotent playbooks, secrets handling.
    • Golden images with Packer; integration with CI for repeatable infra builds.
    Terraform Ansible Packer
    • Microservices portability — image optimization, multi-stage builds, layered caching.
    • Docker networking deep-dive, security scanning, vulnerability hardening.
    • Container registries, image signing, and supply-chain best practices.
    Docker Trivy Cosign
    • Pods, Deployments, Helm charts — CKA/CKAD-level patterns and exam prep.
    • Service mesh with Istio, mTLS, traffic shifting, observability hooks.
    • HPA, KEDA, GPU node pools for AI workloads.
    Kubernetes Helm Istio EKS GKE
    • Shipping with confidence — blue/green deployments, canary releases, feature flags.
    • GitOps with ArgoCD, drift detection, pull-based deployments.
    • Pipeline observability and rollback automation.
    Jenkins GitHub Actions ArgoCD
    • Don't just monitor — observe. Distributed tracing, log aggregation, structured metrics.
    • SLI/SLO design, error-budget runbooks, dashboards practitioners actually use.
    • OpenTelemetry pipelines and unified telemetry across services.
    Prometheus Grafana OpenTelemetry ELK
    • The program USP — training and deploying ML models on K8s, GPU scheduling, autoscaling.
    • Feature stores, model registries, eval pipelines, drift detection.
    • AI-driven anomaly detection over your own telemetry data.
    Kubeflow KServe MLflow Ray
    • Building AI assistants for DevOps — RAG over runbooks, semantic search over incidents.
    • Agentic incident response: pager-on-call agents that triage and remediate autonomously.
    • Cost-safe LLM deployment patterns inside platform infra.
    LangChain LangGraph Pinecone Bedrock
Why EdWagon

Built differently
on purpose.

Four things that make this cohort feel less like a course and more like a serious engineering apprenticeship.

01 · AI-First Teaching

AI tools in the workflow, not just the slides

We don't just teach DevOps — we teach you how to use Cursor, Copilot, and Claude to write better infra-code and ship faster.

02 · 1:1 Mentorship

Weekly office hours with FAANG engineers

Direct access to mentors from Google, Meta, Netflix, LinkedIn — code reviews, system-design dry-runs, and career strategy every week.

03 · Global Network

Peers in India, UAE, Singapore

Join a 24/7 Slack across three timezones — perfect for after-hours debugging, async pair-programming, and warm intros.

04 · Real-World Labs

$200 of cloud credits, production-grade

No "Hello World." Every lab runs on real AWS infrastructure with real failures, real costs, and real on-call patterns.

Projects you ship

Build what the
industry needs.

Four capstone-grade projects woven through the program — each one becomes proof of work in your portfolio and an answer to the next system-design interview.

01

Self-Healing AWS Infrastructure

Build an LLM-agent that detects AWS outages, diagnoses root cause from CloudWatch + logs, and executes safe remediations end-to-end.

LangGraphAWSCloudWatchLambdaTerraform
02

Private LLM on Kubernetes

Deploy Llama 3 on a K8s cluster with KServe, GPU autoscaling, prompt-cache layer, and a cost-guard sidecar.

KubernetesKServeLlama 3HelmPrometheus
03

End-to-end CI/CD for a GenAI App

Ship a Generative AI application with full pipeline — eval gates, canary deploys, drift monitoring, and Pinecone-backed RAG.

GitHub ActionsArgoCDPineconeBedrockLangSmith
04

Multi-Region Disaster Recovery

Architect active-active multi-region failover for a high-traffic fintech app, with chaos drills and a recorded RTO/RPO report.

AWSRoute 53AuroraTerraformChaos Mesh
Mentors

Learn from engineers
shipping AI to production.

100+ senior practitioners — currently building at LinkedIn, Netflix, Google, Meta, Razorpay, and more — review your code, unblock you weekly, and bring judgment that only comes from inside the teams you want to join.

Priya Menon

Senior Software Engineer at LinkedIn

Ex · Microsoft · Stripe
Priya Menon

Vikram Rao

Staff Engineer at Netflix

Ex · Google · NVIDIA
Vikram Rao

Karthik Iyer

Senior PM at Google AI

Ex · Meesho · Microsoft
Karthik Iyer

Meera Pillai

Staff SRE at Meta

Ex · Atlassian · Postman
Meera Pillai

Rahul Sharma

FDE Lead at GovTech Singapore

Ex · Razorpay · Swiggy
Rahul Sharma

Anaya Khanna

Principal Cloud Architect at Razorpay

Ex · Google · PhonePe
Anaya Khanna

Aditya Verma

Staff AI Engineer at Postman

Ex · Razorpay · Swiggy

Sneha Kapoor

Cloud Lead at Swiggy

Ex · Meesho · CRED

Devansh Gupta

Principal Engineer at Cognizant

Ex · Microsoft · Airtel

Tanvi Shah

SRE Lead at Meesho

Ex · Unacademy · Airtel

Kabir Khanna

AI Researcher at Google

Ex · LinkedIn · Microsoft

Ishita Roy

DevOps Lead at Airtel

Ex · Unacademy · Razorpay
Career Outcomes

Our Alumni
Work At.

10K+ AIOps alumni placed across 220+ partner companies — India, UAE, and Singapore.

Microsoft
Google
LinkedIn
Airtel
Razorpay
Postman
Swiggy
Meesho
Unacademy
PhonePe
Cognizant
Postman
Cognizant
Google
LinkedIn
Airtel
Razorpay
Swiggy
Meesho
Unacademy
Microsoft
PhonePe
Free Live Masterclass

How to Optimise GPU Costs on the Cloud

A 90-minute deep-dive into right-sizing GPU clusters, spot vs reserved, multi-tenant inference, and the production patterns the FAANG infra teams actually run.

  • Sat, 15 June 2026
  • 7 PM – 8:30 PM IST
  • Free Registration
Vikram Rao
Featuring Vikram Rao Lead Engineer · NVIDIA
FAQs

Answers to what
applicants ask most.

Do I need a DevOps / SRE background?
Helpful but not required. Most learners come in with backend/cloud/SRE experience, but we admit strong backend engineers and curious analysts too. The bridge module covers Linux + scripting foundations so nobody starts from cold.
How are the labs run — do I need my own cloud account?
Each learner gets $200 in real cloud credits (AWS) to run labs in their own account. We send setup playbooks at week 1 so you can spin up a sandboxed environment without risk of surprise bills.
How much weekly time should I commit?
Plan for 10–12 hours a week: two live sessions (~3 hours), labs (~5 hours), squad debugging (~2 hours). Project weeks are heavier (~15 hours). Most learners hold full-time jobs through the program.
What certificate do I get?
A jointly-signed Professional Certification issued by the TIH Foundation for IoT & IoE at IIT Bombay and the Edzor Centre of AI & Technological Excellence. Verifiable certificate ID, recognised across our 220+ hiring partners. The curriculum is also CKA/CKAD-aligned so you can sit those exams directly after.
Is financing available?
Yes. No-cost EMI from ₹4,500/mo for India learners (up to 12 months). UAE and Singapore learners get split-payment installments across the program. Counsellors walk you through options on the fit call.
What roles do alumni typically move into?
AIOps Engineer, MLOps Engineer, Forward Deployed Engineer, Senior SRE, and Cloud Architect (AI specialisation). Median comp jump in the last cohort was 62% across all three regions.
Cohort 04
Starts 25 June
$200 Cloud Credits
FAANG-grade Mentors
Get Started

Stop maintaining the old stack.

Join the next AIOps cohort — live, hands-on, and built for the AI-first world. Across India, UAE, and Singapore.