Cloud Security Engineer Course in Bangalore — 3 Months
Networkers Home runs Bangalore's most current cloud security engineer specialisation — a 3-month programme structured around the two highest-impact cloud security certifications (AWS Certified Security – Specialty SCS-C02 in Month 1, Microsoft Azure Security Engineer AZ-500 in Month 2) plus a dedicated AI Cloud Security month covering cloud-AI red-teaming (AWS Bedrock, Azure OpenAI), AI agent infrastructure security, LLM cloud-firewall workflows, and a real capstone engagement. ₹50,000 + 18% GST. Placement Guarantee* across 800+ pan-India hiring partners. 45,000+ engineers placed since 2007.
- Fee
- ₹50,000 + 18% GST
- Duration
- 3 Months
- EMI
- 6 × ₹9,834 via NBFC
- Mode
- Online + Classroom
- Next batch
- 1 July 2026
- Lab access
- Real AWS / Azure 24×7
The cloud security engineer role is the highest-demand security specialisation in Bangalore right now.
Through 2024 and into 2026, the Bangalore cybersecurity job market split into specialisations. SOC analyst hiring remained steady at IT services and consulting firms. Penetration tester hiring concentrated at boutique firms and product company red teams. But cloud security engineer hiring — that grew 2-3x faster than any other security specialisation in the city.
The driver is structural. Every Bangalore product company born after 2018 runs on cloud — AWS for the majority, Azure for many, GCP for a smaller but growing slice. Every Bangalore BFSI captive set up after 2020 runs on cloud too — JP Morgan India's cloud platform, Goldman Sachs India's Azure shop, Wells Fargo Bangalore's hybrid cloud — all of them need cloud security engineers who can design IAM properly, configure network segmentation, run SIEM hunting queries in Sentinel or CloudTrail, and stay ahead of new attack patterns. As of mid-2026, Razorpay, Flipkart, Walmart Labs, Cred, Adobe India, and Postman all have open cloud security engineer requisitions running for 60-90 days because the talent simply isn't there.
The talent gap exists because cloud security engineering is genuinely harder to teach than other security specialisations. You can simulate web application security in a free Burp Suite lab. You can simulate network security in a software-only environment. But cloud security work requires real cloud accounts with real billable services, real IAM policy edge cases, real Azure Conditional Access misconfigurations to diagnose. Most Bangalore training institutes don't provide that infrastructure. The result is graduates who know the AWS SCS-C02 exam blueprint but can't actually work in a real cloud security role.
This course was built around the actual infrastructure problem. Real AWS production accounts. Real Azure tenants. Real GCP projects. Students get hands-on with the cloud security tooling that hiring managers expect — AWS Security Hub workflows, Microsoft Sentinel KQL hunting queries, AWS Config Rules, Azure Defender for Cloud, plus the offensive cloud tooling (CloudFox, Pacu, Prowler) that product company red teams use. The certification preparation (Month 1 SCS-C02, Month 2 AZ-500) anchors the curriculum to recognised credentials hiring managers screen for. The Month 3 AI cloud security material covers what's now non-optional for senior cloud security roles at AI-heavy product companies.
3-Month Cloud Security Engineer Curriculum
| Month | Module | Topics | Tools |
|---|---|---|---|
| Month 1 | AWS Security Specialty (SCS-C02) | Threat Detection · Logging · Infrastructure Security · IAM · Data Protection · Governance | AWS Config · CloudTrail · GuardDuty · Security Hub · IAM Access Analyzer · KMS · Prowler · ScoutSuite |
| Month 2 | Microsoft Azure Security Engineer (AZ-500) | Entra ID · Conditional Access · PIM · Azure Firewall · Defender for Cloud · Sentinel SIEM · Key Vault · WAF | Azure CLI · Defender · Sentinel KQL · Key Vault · Azure Policy · Microsoft Purview · ScoutSuite · Prowler |
| Month 3 | AI Cloud Security + Capstone | AWS Bedrock red-team · Azure OpenAI security · AI agent infra · LLM cloud-firewall · capstone engagement | garak · Pyrit · Lakera AI · Promptfoo · CloudFox · Pacu · LangChain security tooling |
AWS Security Specialty (SCS-C02) — Deep Hands-On
Month 1 covers the AWS Certified Security – Specialty (SCS-C02) blueprint in depth. The exam itself maps to six domains, and we structure the month around those six domains plus the hands-on lab work that translates exam knowledge into actual workplace ability. Most students who put in 8-10 hours per week of mock-test preparation on NHPREP.com beyond the live classes clear SCS-C02 within 30-45 days of completing Month 1.
Week 1 — Threat Detection, Logging & Incident Response
AWS GuardDuty configuration and tuning, including the AI-augmented findings introduced in 2024-2025 that materially change the false-positive rate. CloudTrail event ingestion architecture, including dual-layer logging (Management Events + Data Events), CloudTrail Lake for SQL-based audit query workflows, multi-account aggregation via Organizations and the AWS Audit Manager service. AWS Security Hub configuration for cross-service findings consolidation, including custom action workflows for automated response patterns. Detective service for threat investigation — graph-based analysis of GuardDuty findings that's underused in the market but heavily tested on SCS-C02.
Incident response playbook design: detection in CloudWatch / EventBridge, containment via Lambda automation, eradication via Systems Manager Run Command, recovery via Backup and CloudFormation, lessons-learned via Security Hub investigation links. The capstone for Week 1 is designing a detection-and-response runbook for a synthetic incident against the lab AWS account — what hiring managers will test you on in any AWS security interview.
Week 2 — IAM & Identity Federation
AWS IAM at the depth real cloud security work requires — IAM policy evaluation logic (explicit deny, explicit allow, implicit deny, the boundary between identity-based and resource-based policies, permission boundaries, service control policies in Organizations, session policies), policy versioning, IAM Access Analyzer for unused-credential detection and external-access discovery, IAM Identity Center (formerly AWS SSO) for multi-account access patterns. Cross-account access via role assumption, including external-ID patterns for third-party integrations and the AssumeRole-with-WebIdentity flows for OIDC federation.
Identity federation deep dive — SAML 2.0 federation with on-premises Active Directory and Microsoft Entra ID, OIDC federation patterns, Cognito user pool configuration for application-level identity. Authorization-at-scale patterns including ABAC (Attribute-Based Access Control) vs RBAC, IAM tag-based authorization, and the SCS-C02 favourite topic of session tag passthrough across role chains. We cover real misconfigurations that lead to privilege escalation — overly broad iam:PassRole, AssumeRole on wildcard principals, dangerous AccessKey rotation patterns.
Week 3 — Infrastructure Security & Data Protection
VPC security depth — security groups, network ACLs, AWS Network Firewall, AWS WAF (Bot Control, account takeover prevention), Shield Standard vs Shield Advanced. VPC Flow Logs for network-traffic visibility, GuardDuty's VPC-based threat detection, AWS Network Manager for multi-VPC visibility. AWS Verified Access (the zero-trust application access service) and the migration patterns from Client VPN to Verified Access that BFSI captives in Bangalore have been rolling out through 2025-2026.
Data protection at rest and in transit — KMS Customer-Managed Keys vs AWS-Managed Keys, key policy authorisation, grant patterns, multi-region replication for KMS keys, CloudHSM for FIPS 140-2 Level 3 requirements. S3 security — bucket policies, ACLs (legacy but tested), Object Lock for compliance-grade retention, S3 Block Public Access, Macie for PII discovery, server-side encryption variants (SSE-S3, SSE-KMS, SSE-C, DSSE-KMS). RDS encryption, EBS encryption, Secrets Manager for credential rotation, Parameter Store for non-secret configuration. The SCS-C02 exam tests data protection scenarios heavily — we cover every common pattern.
Week 4 — Management, Governance, Compliance + SCS-C02 Mock Run
AWS Config Rules for configuration drift detection, the conformance pack patterns for CIS / NIST / PCI-DSS / HIPAA frameworks, AWS Audit Manager for evidence collection. Organizations + SCPs for guardrail enforcement at the OU level, AWS Control Tower for landing-zone management, Service Catalog for approved-resource patterns. Logging architecture at scale — central logging account patterns with CloudWatch cross-account sharing, OpenSearch / Splunk integration patterns, log retention and archival to S3 Glacier.
Week 4 closes with two full SCS-C02 mock exams under exam conditions (170-minute timed, multiple choice + multi-response). Students who score below 70% on the second mock get personalised gap-analysis support and 30 additional days of NHPREP.com access for catch-up before booking the real exam at Pearson VUE.
Microsoft Azure Security Engineer (AZ-500) — Deep Hands-On
Month 2 covers the Microsoft Azure Security Engineer Associate (AZ-500) blueprint with the same hands-on depth. The AZ-500 exam itself is shorter and slightly more operational than SCS-C02, but Azure security work has its own complexity — particularly around Entra ID (the renamed Azure Active Directory) and the Microsoft Defender / Sentinel SIEM ecosystem. Students typically clear AZ-500 within 30 days of completing Month 2.
Week 5 — Microsoft Entra ID + Identity Management
Microsoft Entra ID (formerly Azure Active Directory) at production-engineering depth — user lifecycle, group-based access management, dynamic groups, Conditional Access policy design and ordering, multi-factor authentication including the FIDO2 hardware key patterns enterprises are rolling out, password protection and smart lockout, identity protection (risk-based detection), Privileged Identity Management (PIM) for just-in-time admin access. Hybrid identity patterns using Entra Connect for on-premises AD synchronisation, federation alternatives, Authentication Strengths configuration. External access management for B2B collaboration and customer identity via Entra External ID.
Application identity — service principals vs managed identities, OAuth 2.0 application registration patterns, consent framework, application permissions vs delegated permissions. Real misconfigurations: over-permissioned managed identities, application secrets in code, weak Conditional Access policies that allow legacy authentication. These are the patterns Azure security interviews routinely test.
Week 6 — Platform Protection (Azure Firewall, Defender for Cloud, NSGs)
Network security in Azure — Network Security Groups vs Application Security Groups, Azure Firewall (basic, standard, premium tiers and when each applies), Azure Firewall Manager for centralised policy at scale, Azure Front Door + WAF policies, Azure DDoS Protection (basic vs standard). VNet peering patterns, private endpoints for PaaS service exposure, service endpoints (legacy but still tested), Azure Bastion for jump-box patterns.
Microsoft Defender for Cloud at depth — Secure Score interpretation and remediation, regulatory compliance dashboard, Defender plans (servers, storage, SQL, containers, app service, key vault, DNS, Resource Manager, APIs), CSPM (Cloud Security Posture Management) features, Defender for DevOps for IaC scanning. The transition from Azure Security Center to Defender for Cloud (renamed 2023, expanded continuously through 2024-2026) is heavily tested on AZ-500.
Week 7 — Security Operations (Microsoft Sentinel + Defender XDR)
Microsoft Sentinel — workspace design, data connector configuration for Azure-native sources (Entra ID, Defender for Cloud, Activity Log, Defender XDR) and external sources (third-party SIEM forwarders, syslog, REST API), analytics rules (scheduled queries, NRT rules, microsoft security rules), hunting queries with KQL (Kusto Query Language), workbooks for investigation, watchlists for known-IOC enrichment, playbooks via Logic Apps for SOAR automation.
KQL deep dive — joins (inner, leftouter, leftsemi), summarisation patterns, time-series aggregation, geo-IP enrichment, common security hunting patterns (brute-force detection, lateral movement, data exfiltration). Real KQL queries used by Microsoft Cyber Defense Operations Center that have been published publicly — we deconstruct and rebuild them in the lab. Microsoft Defender XDR for cross-domain correlation (endpoint, identity, email, cloud apps), and the integration with Sentinel for unified SOC operations.
Week 8 — Data & Application Security + AZ-500 Mock Run
Azure Key Vault — secrets, keys, certificates lifecycle, access policies vs RBAC, soft-delete and purge protection, HSM-backed key options. Encryption patterns — Azure Disk Encryption, Azure Storage encryption with customer-managed keys, Azure SQL Always Encrypted for column-level encryption, Always Encrypted with secure enclaves. Microsoft Purview for data classification, sensitivity labels, DLP policies across cloud services.
Application security in Azure — App Service security configuration (authentication providers, CORS, mTLS), API Management security (subscription keys, OAuth 2.0, mutual TLS, IP filtering, rate limiting), Azure Container Apps security boundaries, AKS security (network policies, pod security standards, Azure Policy for AKS). Week 8 closes with two full AZ-500 mock exams, plus gap-analysis support for any candidate scoring below 70%.
AI Cloud Security + Capstone Engagement
Month 3 covers what makes the Networkers Home cloud security engineer course different from every other cloud security training in Bangalore. The same product companies hiring cloud security engineers are also deploying LLM-based features rapidly through 2025-2026 — Razorpay's AI checkout assistant, Flipkart's product-discovery LLMs, Cred's AI customer support, every BFSI captive's internal AI co-pilot. These deployments require cloud security engineers who understand the AI workload's specific threat model, not just generic cloud security.
Week 9 — Cloud-AI Threat Model + AWS Bedrock Security
The AI-on-cloud threat model — prompt injection escaping into IAM contexts, model extraction via inference API abuse, training data poisoning when deploying RAG architectures, supply chain risks in fine-tuning data pipelines. AWS Bedrock security architecture — Guardrails for content filtering, model invocation logging, Bedrock Knowledge Bases security (private RAG patterns), Bedrock Agents and the IAM boundary for autonomous agent tool-use. AWS Generative AI Security Scoping Matrix as the framework for evaluating any AWS AI deployment.
Week 10 — Azure OpenAI Security + Cloud-AI Red-Teaming
Azure OpenAI service security — Content Safety configuration, Azure AI Foundry (formerly Azure AI Studio) security baselines, network isolation patterns for Azure OpenAI deployments, customer-managed encryption for Azure OpenAI data at rest. Microsoft Pyrit framework introduction for systematic AI red-teaming on Azure OpenAI deployments. garak introduction for cross-cloud LLM red-teaming. Lakera AI for LLM firewall testing from both attacker and defender perspectives.
Cloud-AI red-teaming methodology — applying OWASP LLM Top 10 in the cloud context, the cloud-specific portions of LLM07 (Insecure Plugin Design), LLM08 (Excessive Agency), and LLM10 (Model Theft). Real attack chains against Bedrock and Azure OpenAI deployments — how a prompt injection becomes a cloud privilege escalation when the LLM has IAM-backed tool access.
Week 11 — Agentic AI Infrastructure Security
Agent infrastructure security — when an LLM application uses LangChain / AutoGen / CrewAI to take multi-step actions, the cloud security engineer's responsibility extends to: which IAM credentials the agent's tool calls run under, network egress restrictions on agent infrastructure, audit logging of agent decisions and actions, prompt-chain integrity protection, tool-call authorisation patterns, and the supply-chain security of agent tool definitions and system prompts. Hands-on labs include securing a LangChain agent deployment on AWS Lambda, securing an AutoGen multi-agent setup on Azure Container Apps, and designing safe IAM boundaries for an agent that needs limited cloud access.
Week 12 — Capstone Engagement
The capstone is the centerpiece. Each student receives a real cloud security engagement against one of the founder-owned product companies — BrowserFog, AgentFog, QSecure, 24Observe, or QSecNiti — all running real AWS or Azure deployments with real production traffic. The engagement is structured as a real cloud security assessment — IAM review (including detecting over-permissioned principals and missing IAM Access Analyzer findings), network security review (security groups, network ACLs, public exposure), data protection assessment (S3 / Azure Storage public access, KMS / Key Vault configuration), secret scanning (Secrets Manager / Key Vault hygiene plus IaC secret leaks), configuration drift detection (AWS Config / Azure Policy compliance state), AI workload security review (Bedrock or Azure OpenAI deployments).
Deliverable is a written cloud security assessment report in industry-standard format — executive summary for non-technical stakeholders, technical findings with CVSS scoring, remediation guidance including Infrastructure-as-Code patches where applicable. Students present findings to the actual engineering team that owns the target deployment. The engagement earns a verified 1-month cloud security work-experience certificate — and the assessment report itself becomes a centerpiece resume artefact.
Cloud Security Tools Deep-Dive
Every tool below is in active production use at Bangalore product companies and BFSI captives as of 2026-06. We don't teach obsolete tools to fill curriculum hours.
| Tool | Purpose | Cloud | Why it matters |
|---|---|---|---|
| ScoutSuite | Multi-cloud security posture assessment | AWS / Azure / GCP | Foundation tool for any cloud-security pentest engagement |
| Prowler | AWS / Azure / GCP security best-practice scanner | Multi-cloud | Compliance + CIS Benchmark assessment industry-standard |
| CloudFox | AWS attack-surface mapping for offensive security | AWS | What attackers use to map your AWS estate after credential compromise |
| Pacu | AWS exploitation framework | AWS | Active AWS attack simulation — for understanding what AWS attackers can do |
| CloudSploit / Aqua | Cloud security posture management | Multi-cloud | Continuous monitoring for misconfiguration drift |
| Steampipe | SQL-based cloud inventory + compliance queries | Multi-cloud | Modern declarative cloud security assessment workflow |
| AWS Security Hub + Config | Native AWS security posture + compliance | AWS | Tested heavily on SCS-C02 exam — operational necessity post-exam |
| Microsoft Defender for Cloud | Azure-native cloud security posture | Azure | Tested heavily on AZ-500 — operational necessity at any Azure shop |
| Microsoft Sentinel (KQL) | Cloud SIEM + threat hunting | Azure | Hands-on KQL hunting queries — interview must-have for Azure cloud-sec roles |
| AWS Bedrock Guardrails | AI model safety + content filtering on AWS | AWS AI | Cloud-AI security baseline — what every AWS AI deployment must consider |
| Azure OpenAI Content Safety | AI content filtering on Azure | Azure AI | Cloud-AI security baseline for Azure AI deployments |
| Lakera AI | LLM firewall + red-team API (commercial) | Multi-cloud AI | Test prompt-injection defences on cloud-hosted LLMs from both sides |
Who Hires Cloud Security Engineers in Bangalore
Razorpay Cloud Security, Flipkart Cloud Platform Security, Walmart Labs Cloud Security, Cred Infra Security, Postman Security, Adobe India Cloud Security, Atlassian Cloud Security
AWS India, Microsoft Azure India, Google Cloud Bangalore — direct hires for security engineering
JP Morgan India Cloud Platform, Goldman Sachs India Cloud Engineering, Deutsche Bank India Cloud Platform, Wells Fargo Bangalore Cloud Security
KPMG India Cloud, EY India Cloud Cyber, Deloitte India Cloud, TCS Cyber, Wipro Cloud Security, HCL Cyber, Inflow Technologies
Cisco India Cloud Security, Palo Alto Networks India (Prisma Cloud), Wiz, Lacework, Aqua Security partners
Networkers Home has placed 45,000+ engineers since 2007 across the cyber security and networking industry. Placement Guarantee* with written terms at /placement-guarantee-terms/. For cloud security specifically, the placement team maintains direct relationships with the cloud security hiring managers at the named companies and coordinates interview drives multiple times per quarter.
Cloud Security Engineer Salary in Bangalore — 2026
Salary bands compiled from public job postings on Naukri, LinkedIn, and InstaHyre across 2025-2026, plus offer letters shared by alumni for benchmark calibration. Role ranges, not specific outcome promises. Cloud security commands a 15-30% premium over equivalent general-cybersecurity roles in the Bangalore market.
| Role | Experience | Salary band | Typical hirers |
|---|---|---|---|
| Entry-level Cloud Security Engineer (single cert) | 0-1 yr | ₹8-14 LPA | Razorpay, Flipkart, Wipro Cloud Security, KPMG Cloud |
| Cloud Security Engineer (AWS + Azure dual cert) | 1-2 yr | ₹14-22 LPA | Microsoft Azure India, AWS India, Walmart Labs, Adobe India |
| AI Cloud Security Engineer | 2-3 yr | ₹18-28 LPA | Razorpay, Cred, Microsoft AI Bangalore, Google Bangalore |
| Senior Cloud Security Engineer / Architect | 5+ yr | ₹28-45 LPA | Product cos, BFSI captives, consulting firm cloud teams |
| Principal Cloud Security / Cloud Security Architect | 8+ yr | ₹45-70 LPA | Senior IC roles at product companies + BFSI |
Cloud Security Certifications & Frameworks Covered
AWS Certified Security – Specialty (SCS-C02)
Month 1 maps directly to the AWS Security Specialty blueprint — all six domains covered with hands-on labs in real AWS production accounts. Voucher booked separately at Pearson VUE (~$300 USD). Most students clear within 30-45 days post-Month 1. AWS Security Specialty is the highest-impact AWS-specific cert for cloud security careers in Bangalore.
Microsoft Azure Security Engineer (AZ-500)
Month 2 maps to the AZ-500 blueprint — identity and access management, platform protection, security operations, data and application security. Voucher (~$165 USD) booked at Pearson VUE. Combined SCS-C02 + AZ-500 is the dual-cloud cert combo that signals serious cloud security depth on a resume.
(ISC)² CCSP — Certified Cloud Security Professional
Covered at awareness level. CCSP is more enterprise-policy focused than the hands-on SCS-C02 / AZ-500 path we emphasise. Many students take CCSP after 2-3 years of cloud security work for senior architect roles. The course gives enough foundation to study toward CCSP independently.
OWASP Top 10 for LLMs + AI Cloud Security frameworks
Month 3 covers the OWASP LLM Top 10 in the cloud context — how each LLM threat manifests when the model is hosted on AWS Bedrock, Azure OpenAI, or GCP Vertex AI. Plus the AWS Generative AI Security Scoping Matrix, Azure AI security baseline, and NIST AI RMF for compliance-aware cloud AI deployments.
Why Networkers Home for Cloud Security
Networkers Home was founded in Bangalore in 2007 by Vikas Swami, who holds dual CCIE certification (#22239 in both Routing & Switching and Security). Over 19 years of operation, the institute has placed 45,000+ engineers across the cyber security and networking industry, with 800+ active hiring partner relationships.
For cloud security specifically, the institute's edge rests on three things. First, the lab is real cloud — real AWS production accounts, real Azure tenants, real GCP projects with real billable services. Students get to make real IAM mistakes against real consequences and develop the instincts that lab-simulator environments can't replicate. Most Bangalore institutes can't provide this because the AWS / Azure billing cost is prohibitive at scale.
Second, the founder's product portfolio runs on the same cloud infrastructure students are training on. BrowserFog, AgentFog, QSecure, 24Observe, and QSecNiti all run real AWS or Azure deployments with real production traffic. The capstone engagements happen against these real targets — meaning students get a verified work-experience reference for their resume that reflects actual cloud security work, not a simulated exercise. No other Bangalore institute can match this.
Third, the AI cloud security curriculum (Month 3) is unique. Most Bangalore cloud security training stops at AWS SCS-C02 + Azure AZ-500 — the certification path. Cloud security work at AI-heavy product companies needs more — and that's what Month 3 delivers. The Bangalore alumni who land roles at Microsoft AI Bangalore, Razorpay AI Cloud Security, or Cred Infra Security cite the Month 3 content as the differentiator that got them through interviews.
Real Cloud Lab Access — AWS + Azure + GCP
Lab access for the cloud security engineer course bundles real production cloud accounts — not simulators, not sandboxes with restricted services, not lab environments with synthetic data. AWS accounts have real billable services activated (KMS, GuardDuty, Security Hub, Detective, Macie, Bedrock for AI labs, Config, CloudTrail Lake, IAM Access Analyzer). Azure tenants have real Entra ID, Defender for Cloud, Sentinel workspaces, Key Vaults, Azure OpenAI deployments, AKS clusters. GCP projects have real IAM, Security Command Center, Cloud Armor, Vertex AI for AI labs.
Access is 24×7. In-person students get walk-in cloud lab access at the HSR Sector 6 campus Monday through Saturday 11 AM-7 PM. Online students get equivalent access via lab dashboards — login to real AWS / Azure / GCP environments from anywhere. Cloud services consumed in lab work are pre-paid by the institute as part of the course fee — students don't pay AWS / Azure billing separately. Lab credits have been sized so students can run real workloads (deploy real Bedrock models for red-teaming, spin real Azure OpenAI deployments for security review) without hitting quota walls during exercise execution.
Who Teaches the Cloud Security Engineer Course
Month 1 (AWS SCS-C02) is delivered by senior AWS practitioners holding active AWS Security Specialty certifications plus the AWS Solutions Architect Professional. The lead Month 1 trainer has 10+ years of AWS engineering practice across Bangalore product companies and currently advises two product startups on cloud security architecture in the early-stage stage.
Month 2 (Azure AZ-500) is delivered by a trainer holding active AZ-500 plus Microsoft 365 Security Administrator and Microsoft Sentinel certifications, with 8+ years of Azure security engineering practice including roles at one of the BFSI captives. Microsoft Sentinel KQL hunting query depth is one of their published areas of expertise.
Month 3 (AI Cloud Security) is co-delivered by Vikas Swami (Founder, Dual CCIE) and a senior trainer specialising in cloud-AI security and agent infrastructure. The Month 3 trainer's background includes active contribution to OWASP AI Security guidance and red-team engagement work for Bangalore product companies. Real practitioners, not full-time instructors disconnected from current cloud security work.
Placement Guarantee* for Cloud Security Engineers
Placement Guarantee* applies to the Cloud Security Engineer course with written terms at /placement-guarantee-terms/. Terms apply: 90%+ attendance, completion of the capstone cloud security engagement with a satisfactory report deliverable, and active participation in placement drives. The placement team coordinates resume review (cloud security specific framing matters), mock interviews focused on cloud security scenarios (IAM policy analysis interviews, KQL hunting query interviews, AWS Security Hub workflow interviews), and live interview drives across the cloud-focused hiring partners.
For cloud security graduates specifically, the placement team's strongest relationships are with the cloud-native product companies and the BFSI captives that have invested heavily in cloud platform security. Razorpay, Flipkart, Walmart Labs, Adobe India, JP Morgan India, and Goldman Sachs India cloud platform teams have been the most active hirers from this programme. AWS India and Microsoft Azure India also recruit from our alumni network — though their hiring bar is higher and typically requires SCS-C02 + AZ-500 both cleared.
Who Can Take This Course
Eligibility is open to any graduate of any discipline (B.Tech, BCA, B.Sc, B.Com, B.A, BBA, MBA, M.Tech, M.Sc), final-year students of any undergraduate or postgraduate programme, and working professionals across IT and security functions. No prior cloud security experience required.
What does help: basic cloud familiarity at the AWS Cloud Practitioner or Microsoft AZ-900 level. If you have neither, we provide a free 3-week pre-course track on NHPREP.com covering AWS and Azure fundamentals. Software developers with backend AWS / Azure experience often progress faster than non-IT students — about 30% of cohorts are developer-background transitioning into cloud security.
Working professionals make up about 50% of cohorts — typically AWS / Azure engineers wanting to add security depth, or security engineers wanting to specialise in cloud platforms. Weekend intensive batches (Saturday-Sunday 10 AM-2 PM IST) work for this audience and avoid weekday work conflicts. Many alumni from Cisco India, Wipro EC, Infosys EC, IBM ITPL, and the BFSI captives have taken this course while staying full-time employed.
Next Batch Dates & Pricing
Pricing locked at ₹50,000 + 18% GST = ₹59,000 total. Pay one-time via UPI / NEFT / credit card, or set up 6 monthly EMIs of ₹9,834 via NBFC partners. Receipt and access credentials (including cloud lab dashboards) issued within 24 hours of payment. Pre-course NHPREP.com access begins immediately. Seats per batch capped at 20 for individual cloud lab attention.
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Ready to become a Cloud Security Engineer?
3 months · ₹50,000 + 18% GST · AWS SCS-C02 + Azure AZ-500 + AI Cloud Security · capstone real cloud engagement · Placement Guarantee* across 800+ hiring partners. Next batches start 1 July 2026 and 8 July 2026.