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JD #2248
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Associate Software Engineer (JavaScript)

sdwot.ai

  • Hyderabad, Telangana
  • Up to β‚Ή5 LPA
  • Fresher (0-1 Yrs)
  • Posted Oct 26, 2026
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About the role

SD WoT (Smart Digital World of Technology) is an emerging technology solutions provider based in Hyderabad. The company focuses on building AI‑driven platforms, web applications and cloud services for enterprises across India. With a small but highly motivated team, SD WoT encourages a culture of rapid learning, open collaboration and ownership of end‑to‑end product development. The firm has been expanding its footprint in the Hyderabad tech corridor, offering fresh talent a chance to work on real‑world projects from day one. As a fresher‑friendly organization, SD WoT invests heavily in mentorship programs, regular tech talks and hands‑on workshops. Employees get exposure to the full software development lifecycle, from requirement gathering to deployment and post‑release monitoring. The company’s emphasis on modern JavaScript ecosystems makes it an ideal launchpad for graduates eager to master full‑stack development. **Role Summary** The Associate Software Engineer (JavaScript – Fresher) will join the core development team and contribute to building scalable web applications. Reporting to senior engineers, the candidate will assist in translating business requirements into clean, maintainable code, while learning best practices in version control, testing and agile delivery. This role is designed for recent engineering graduates who have a solid foundation in programming and a keen interest in JavaScript‑based technologies. **Key Responsibilities** 1. Participate in requirement analysis sessions and help draft technical specifications. 2. Write, test, and debug JavaScript code for front‑end and back‑end components. 3. Develop UI features using HTML5, CSS3 and modern JavaScript frameworks. 4. Assist in building RESTful APIs with Node.js and integrate them with front‑end modules. 5. Contribute to database design and queries using MongoDB or similar NoSQL stores. 6. Perform unit testing and support QA activities to ensure high‑quality releases. 7. Collaborate with senior developers to perform code reviews and adopt coding standards. 8. Document code, APIs and deployment procedures for future reference. 9. Participate in sprint planning, daily stand‑ups and retrospective meetings. 10. Stay updated with emerging JavaScript trends and propose improvements to the existing stack. **Tech Stack** The primary technologies include JavaScript (ES6+), Node.js, Express.js, React.js, MongoDB, Git, Linux command line, and basic DevOps tools. Knowledge of HTML5, CSS3, and optional exposure to TypeScript or Redux will be advantageous. **Growth Path** Starting as an Associate Engineer, high performers can progress to Software Engineer, Senior Engineer, and eventually Tech Lead or Solution Architect roles within 2‑4 years. The company encourages continuous learning through certifications, internal hackathons and cross‑functional project assignments. **Why Join SD WoT?** - Direct mentorship from industry‑experienced engineers. - Hands‑on experience with the full MERN stack on live client projects. - Competitive salary up to β‚Ή5β€―LPA with performance‑linked increments. - Friendly, inclusive work environment with a focus on work‑life balance. - Opportunity to grow quickly in a fast‑moving startup setting while contributing to impactful products.

Eligibility & process

Who can apply

β€’ Minimum qualification: B.E. / B.Tech. in Computer Science, Information Technology, Electronics & Communication, or Electrical Engineering. β€’ No specific percentage requirement mentioned; generally a minimum of 60% aggregate is preferred. β€’ Fresh graduates from the 2024‑2026 batch are eligible. β€’ Strong problem‑solving and analytical abilities. β€’ Basic programming knowledge in C, C++, Python or any other backend language. β€’ Fundamental understanding of HTML5, CSS3 and JavaScript. β€’ Self‑motivated, proactive, eager to learn and adapt. β€’ No active backlogs at the time of joining.

Skills & stack

JavaScript HTML5 CSS3 C C++ Python MERN Stack Node.js React.js Unix/Linux Database Systems Operating Systems Computer Networks

Selection process

  1. Round 1: Online Aptitude Test
  2. Round 2: Technical Interview (JavaScript, Data Structures & Algorithms)
  3. Round 3: HR Interview

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 (JavaScript, HTML5, CSS3, C, C++, Python, MERN Stack, Node.js, React.js, Unix/Linux, Database Systems, Operating Systems, Computer Networks) & 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 sdwot.ai 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 sdwot.ai as a Associate Software Engineer (JavaScript)?
Highlight sdwot.ai's market reputation, recent tech innovations, and how your skills in JavaScript 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.
sdwot.ai Up to β‚Ή5 LPA
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