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Graduate Trainee - Cyber Security Tool Engineer - Blue Team

Cyberaxislabs

  • Hyderabad
  • 3.5 LPA
  • Fresher (0-1 Yrs)
  • Posted Today
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About the role

CyberAxis Labs is a fast‑growing cybersecurity services firm headquartered in Hyderabad, India. Founded by a team of seasoned security professionals, the company offers end‑to‑end protection services ranging from threat hunting and incident response to managed security operations for clients across banking, e‑commerce, and telecom sectors. With a strong focus on innovation, CyberAxis Labs continuously invests in the latest security platforms, automation frameworks, and threat intelligence feeds, creating a vibrant ecosystem where fresh talent can work alongside industry veterans. The organization prides itself on a collaborative culture that encourages learning, experimentation, and rapid skill acquisition, making it an attractive destination for recent graduates eager to launch a career in cyber defence. The Graduate Trainee – Cyber Security Tool Engineer – Blue Team role is a structured 24‑month program designed to transform academically strong candidates into competent security practitioners. Trainees will receive hands‑on exposure to industry‑standard tools such as SIEM (Splunk, QRadar), EDR/XDR platforms (CrowdStrike, SentinelOne), SOAR solutions, vulnerability scanners, and email security gateways. The program is split into two 12‑month phases: the first year focuses on foundational training, lab exercises, and participation in live client projects under supervision; the second year deepens expertise through advanced use‑case development, automation scripting, and leadership of small‑scale security initiatives. Successful completion may lead to a full‑time position as a Security Analyst or Engineer, depending on performance. Key responsibilities include: 1. Deploy, configure, and maintain SIEM, EDR/XDR, antivirus, vulnerability scanners, and email security solutions. 2. Monitor security alerts, dashboards, and logs to detect suspicious activities. 3. Create, tune, and validate detection and correlation rules, dashboards, and use cases. 4. Support endpoint security operations – agent installation, policy configuration, health checks, and troubleshooting. 5. Perform log analysis across Windows, Linux, network, firewall, and application sources. 6. Assist in vulnerability assessments and remediation tracking. 7. Participate in internal and client‑facing Blue Team projects under mentorship. 8. Stay updated on emerging threats, attack techniques, and new security technologies. 9. Document findings, prepare incident reports, and contribute to knowledge‑base articles. 10. Collaborate with cross‑functional teams to improve overall security posture. Tech stack exposure includes SIEM platforms (Splunk, QRadar), EDR/XDR tools (CrowdStrike, SentinelOne), SOAR (Cortex XSOAR), scripting languages (Python, Bash), and cloud security services (AWS GuardDuty, Azure Sentinel). The program emphasizes practical skill development, critical thinking, and effective communication. Growth path: After the 2‑year commitment, high‑performing trainees are offered full‑time roles such as Security Analyst, SOC Engineer, or Threat Intelligence Associate, with clear promotion tracks to Senior Analyst, Team Lead, and eventually Managerial positions. Continuous learning is supported through certifications (CompTIA Security+, CEH, Splunk Core) and internal workshops. Why join CyberAxis Labs? The company offers a real‑world, tool‑centric learning environment, mentorship from seasoned security experts, and a clear roadmap to a rewarding cyber‑defence career. Graduates gain confidence handling live incidents, building detection logic, and contributing to client security outcomesβ€”all while being part of a supportive, growth‑focused culture.

Eligibility & process

Who can apply

Any graduate or diploma holder (B.Tech/B.E., B.Sc., B.Com, etc.) with a specialization in Cybersecurity preferred. Minimum 60% aggregate (or CGPA 6.5/10) in the qualifying degree. Graduation year must be 2026 or earlier. No active backlogs at the time of joining. Candidates should possess basic knowledge of networking, Windows and Linux operating systems, and a keen interest in security monitoring and incident response.

Skills & stack

SIEM EDR/XDR SOAR log analysis Windows Linux networking fundamentals vulnerability assessment incident response basics Python scripting strong written and verbal communication in English

Selection process

  1. Round 1: Online Aptitude Test
  2. Round 2: Technical Interview (hands‑on tool questions, scenario‑based problem solving)
  3. Round 3: HR Interview (fitment, motivation, commitment to 2‑year program)

Prep kit

19 resources
Study material 4
Company-specific guides 4
Likely coding questions 4
Round-wise strategy 4
Round 1: Online Assessment (OA) Aptitude, Quantitative Logic & 2 Coding Problems Focus on accuracy and speed. Practice arrays, strings, and standard arithmetic puzzles.
Round 2: Technical Interview 1 Core Tech Stack (SIEM, EDR/XDR, SOAR, log analysis, Windows, Linux, networking fundamentals, vulnerability assessment, incident response basics, Python scripting, strong written and verbal communication in English) & Live Code Tracing Explain your thought process aloud. Analyze time & space complexities before coding.
Round 3: System Design & Problem Solving Database Schemas, APIs & Architecture Basics Clarify edge cases, diagram schemas cleanly, and discuss scalability trade-offs.
Round 4: HR & Cultural Fit Discussion Cyberaxislabs Core Values, Learning Agility & Offer Terms Demonstrate passion, strong communication, and readiness for full-time collaboration.
Technical questions 4
What is the bias-variance tradeoff and how do you prevent overfitting? Answer
Model answer: High bias leads to underfitting (oversimplified model), high variance leads to overfitting (captures noise). Mitigate using L1/L2 Regularization, Dropout, Cross-Validation, and data augmentation.
Explain the difference between Precision, Recall, and F1-Score. Answer
Model answer: Precision = TP / (TP + FP) (correctness of positive predictions). Recall = TP / (TP + FN) (coverage of actual positives). F1-Score is the harmonic mean of Precision and Recall.
How does Gradient Descent work and what is the role of Learning Rate? Answer
Model answer: It optimizes loss functions by iteratively moving weights in the direction of negative gradient. A large learning rate may overshoot the minimum; a small rate causes slow convergence.
What is the difference between Supervised, Unsupervised, and Self-Supervised learning? Answer
Model answer: Supervised uses labeled data (X -> y). Unsupervised finds hidden patterns in unlabeled data (clustering/PCA). Self-supervised generates labels from input data (e.g. masked language modeling in BERT/Transformers).
Behavioural & HR questions 3
Why do you want to join Cyberaxislabs as a Graduate Trainee - Cyber Security Tool Engineer - Blue Team?
Highlight Cyberaxislabs's market reputation, recent tech innovations, and how your skills in SIEM directly solve their team's objectives.
Describe a challenging bug or academic project roadblock and how you resolved it.
Use the STAR method: Situation (project context), Task (what needed solving), Action (specific tools/logic applied), Result (quantifiable positive outcome).
How do you handle strict deadlines or sudden scope changes?
Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.
Cyberaxislabs 3.5 LPA
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