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REQUIREMENT_ID_1765 • 3-DAY_ACTIVE_POLICY JD

Specialist Programmer (Trainee)Infosys

Company
Company Infosys
Type
Opportunity Type Internship
Salary
Stipend / Salary ₹11-21 LPA per annum
Location
Location Bengaluru, India
Posted Date
Posted Date Today
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Java Scala React.js Angular.js Node.js Express.js MongoDB Cassandra Hadoop Hive Spark Storm Kafka Spark MLlib Azure ML Python Generative AI Spring Boot Cloud Foundry Docker Kubernetes Jenkins Git Jira Maven Gradle Puppet Chef Akka Play Functional Programming AI/ML
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Aptitude Practice Questions Open Resource ↗
Curated quantitative and logical reasoning problems to sharpen the aptitude section of the online assessment.
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Company Interview Preparation Guide Open Resource ↗
Comprehensive guide covering typical interview patterns, coding challenges, and HR questions for roles at Infosys.
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Comprehensive Interview Prep Resource Open Resource ↗
Structured notes and mock interview scripts to help candidates practice technical and behavioral rounds effectively.
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Algorithm Practice Problems Open Resource ↗
Extensive problem set to improve coding speed and accuracy, essential for the coding assessment stage.

UG/PG graduates of 2024, 2025 or 2026 batches. Degrees accepted: B.Tech/B.E., MCA, M.Tech, MS/M.Sc in any specialization. Minimum aggregate 60% (or CGPA 6.0/10). No active backlogs at the time of joining. Up to 2 years of relevant experience in Java micro‑services, Big Data, ML, or related domains is acceptable. Strong programming fundamentals and problem‑solving ability are mandatory.

1
Round 1: Online coding assessment (DSA & aptitude)
2
Round 2: Technical interview (core programming, system design, tech stack)
3
Round 3: HR interview (fitment, communication, career goals)
Infosys Limited is one of India’s largest IT services and consulting firms, serving Fortune 500 clients across banking, retail, manufacturing, and emerging technology domains. With a presence in more than 50 countries, Infosys has built a reputation for delivering end‑to‑end digital transformation solutions, leveraging cloud, AI, and data‑driven platforms. The company invests heavily in up‑skilling its workforce through the Infosys Learning Platform and encourages a culture of continuous innovation, making it an attractive destination for fresh engineering graduates. The role of Specialist Programmer (Trainee) is designed for recent UG/PG graduates who have a strong foundation in programming and are eager to work on full‑stack, enterprise‑grade applications. As a trainee, you will be part of an Agile delivery team that builds scalable micro‑services, data pipelines, and AI‑enabled features for large‑scale digital marketplaces. You will get exposure to modern development frameworks, cloud‑native architectures, and DevOps practices while contributing from requirement gathering to production deployment. **Key Responsibilities** 1. Design, develop, and maintain Java‑based micro‑services using Spring Boot, Cloud Foundry, and Docker containers. 2. Build front‑end interfaces with React.js, Angular.js, or Node.js/Express.js, ensuring responsive and performant user experiences. 3. Implement big‑data pipelines using Hadoop, Hive, Spark, Storm, and Kafka, and apply machine‑learning models via Spark MLlib or Azure ML. 4. Write functional code in Scala, leveraging Akka and Play frameworks for reactive programming. 5. Participate in code reviews, unit testing, and performance tuning to achieve zero‑defect delivery. 6. Automate build, test, and deployment workflows using Maven/Gradle, Jenkins, Git, and Kubernetes/Mesos. 7. Collaborate with cross‑functional teams—product, QA, and operations—to deliver end‑to‑end solutions. 8. Contribute to open‑source projects and internal tech user groups, fostering a culture of knowledge sharing. 9. Stay updated with emerging technologies such as generative AI, IoT, and serverless computing, proposing innovative solutions for client problems. 10. Document technical designs, APIs, and deployment procedures for future reference and compliance. **Technology Stack**: Java, JEE, Spring Boot, Cloud Foundry, Docker, Kubernetes, Scala, Akka, Play, React.js, Angular.js, Node.js, Express.js, MongoDB, Cassandra, Hadoop, Hive, Spark, Storm, Kafka, Spark MLlib, Azure ML, Python, Generative AI, Puppet, Chef, Jenkins, Git, Jira, Maven, Gradle. **Growth Path**: Trainees start as Specialist Programmer L1 (₹10 LPA + ₹1 Lakh joining bonus) and can progress to L2 (₹16 LPA) and L3 (₹21 LPA) within 2‑3 years based on performance, skill acquisition, and project impact. Successful contributors may move into senior developer, lead architect, or solution specialist roles, with opportunities to work on flagship digital platforms for Fortune 500 clients. **Why Join Infosys**: Infosys offers a structured learning ecosystem, global exposure, and the chance to work on cutting‑edge technologies that shape the future of enterprise software. The hybrid work model provides flexibility while maintaining strong mentorship and collaboration. Fresh talent gets a clear career roadmap, competitive compensation, and a vibrant community that celebrates innovation and diversity.

Infosys — AI & Machine Learning Interview Guide

Previously asked questions, exam syllabus, coding benchmarks & round strategy.

APTITUDE & LOGIC 📖
Aptitude Practice Questions & Online Mock Tests

Curated logical, quantitative, and verbal reasoning problems to sharpen reasoning skills required for the initial screening test.

Open Resource ↗
COMPANY GUIDE 🎯
Infosys Interview Preparation Corner

Comprehensive guide covering typical interview formats, common questions, and preparation tips for Infosys and off-campus tech roles.

Open Resource ↗
MOCK TESTS & PAPERS 📝
Comprehensive Interview Prep Resources & Syllabus

Collection of previous year questions, company-specific test patterns, and interview experiences for technical and HR rounds.

Open Resource ↗
CODING PRACTICE 💻
Algorithm and Data Structure Problem Set

Practice problems to improve coding proficiency and algorithm problem-solving speed for technical rounds.

Open Resource ↗
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 (Java, Scala, React.js, Angular.js, Node.js, Express.js, MongoDB, Cassandra, Hadoop, Hive, Spark, Storm, Kafka, Spark MLlib, Azure ML, Python, Generative AI, Spring Boot, Cloud Foundry, Docker, Kubernetes, Jenkins, Git, Jira, Maven, Gradle, Puppet, Chef, Akka, Play, Functional Programming, AI/ML) & 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
Infosys Core Values, Learning Agility & Offer Terms
Demonstrate passion, strong communication, and readiness for full-time collaboration.
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).
Why do you want to join Infosys as a Specialist Programmer (Trainee)Infosys?
Preparation Tip: Highlight Infosys's market reputation, recent tech innovations, and how your skills in Java directly solve their team's objectives.
Describe a challenging bug or academic project roadblock and how you resolved it.
Preparation Tip: 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?
Preparation Tip: Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.

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