Live opening · Posted 2 days ago

Instructor - D&R

GRAMAX · Bhubaneswar, Odisha, India (On-site)
Linkedin No
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At a glance

The key details from the original listing.

Posted 2 days ago
CompanyGRAMAX
LocationBhubaneswar, Odisha, India (On-site)
Work modeNo
SkillsPython, Pandas, TensorFlow
SourceLinkedin
ListedPosted 2 days ago

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About the role

Description supplied by the original job listing.

Key Responsibilities
Plan, design and deliver D&R training sessions with hands-on labs and assessments
Train learners on penetration testing, including vulnerability assessment, penetration-testing methodologies, web and network security testing, exploitation in authorised labs, and reporting and remediation
Cover red teaming, including adversary simulation, attack-path analysis, reconnaissance, controlled attack execution and MITRE ATT&CK mapping
Teach Wi-Fi penetration testing, including wireless security assessment, Wi-Fi protocols, encryption standards, access-point security, wireless traffic analysis and authorised wireless attack simulations
Train learners on blue teaming and defensive security operations, including log analysis, threat detection, threat hunting, detection engineering, security monitoring, log correlation and defensive control validation
Explain SOC implementation, including SOC architecture, SIEM onboarding, log-source integration, use-case development, alert triage, escalation workflows, SOC KPIs and operational procedures
Cover threat intelligence, including the intelligence lifecycle, IOC analysis, threat actor profiling, TTP mapping, threat feeds, and intelligence sharing using STIX/TAXII and MITRE ATT&CK
Cover incident response and digital forensics, including incident triage, containment, eradication, recovery, evidence preservation, forensic investigation, root-cause analysis and post-incident reporting
Teach SOAR automation, including automating detection, triage and response workflows
Teach patch and configuration management, including asset inventory, vulnerability prioritisation, patch deployment, configuration baselines, hardening, compliance checks and remediation validation
Cover risk assessment, business continuity and disaster recovery, including Business Impact Analysis (BIA), RTO/RPO, backup and recovery strategies, disaster recovery planning, testing and business continuity exercises
Demonstrate AI for cybersecurity, using Python and machine learning for anomaly detection, security-log analysis, threat classification, threat detection and detection automation
Track batch attendance, performance and feedback, and resolve learner doubts
Coordinate with internal teams to complete schedules on time
Required Skills
Offensive Security: penetration testing, vulnerability assessment, red teaming and Wi-Fi security assessment tools
Defensive Security: blue teaming, threat hunting, detection engineering, SIEM use-case development and SOC operations
SOC Engineering & Monitoring: SIEM deployment and integration, log onboarding, detection rules, alert triage and SOC workflow design; tools such as Splunk, ELK Stack, Graylog, Security Onion, Sysmon, Osquery, Velociraptor
Network Detection: Wireshark, Nmap, Snort, Suricata, Zeek, Arkime, pfSense, iptables
Threat Intelligence: IOC enrichment, MITRE ATT&CK, STIX/TAXII, threat feeds and intelligence platforms such as MISP, Yeti, OpenTAXII, OTX, STIX tools
Endpoint & DLP: CrowdStrike Falcon, OpenDLP, MyDLP, UEBA tools
Incident Response, SOAR & Forensics: digital evidence handling, memory and disk forensics, incident investigation and recovery; tools such as Cortex XSOAR, Splunk Phantom, TheHive, Autopsy, Volatility, Ghidra
Patch & Configuration Management: vulnerability remediation, system hardening, configuration compliance and patch automation; tools such as WSUS, Automox, OpenSCAP, Ansible, Puppet, Chef, SaltStack
Risk, Business Continuity & Recovery: risk assessment, BIA, RTO/RPO, backup validation, disaster recovery, recovery testing, backup and cloud disaster recovery, CASB, CSPM
AI for Cybersecurity & Data Science: Python-based security analytics, data processing, anomaly detection and basic machine-learning model development; tools such as Python, Pandas, NumPy, Scikit-learn, TensorFlow, Jupyter, Flask
Practical Training Delivery: ability to configure lab environments, demonstrate tools, develop assessments and guide learners through controlled exercises
Strong communication and facilitation skills.

Work arrangement
No

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