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REQUIREMENT_ID_162 • 3-DAY_ACTIVE_POLICY

Software Engineer / Product Role

Company
Company Proarch
Type
Opportunity Type Internship
Salary
Stipend / Salary Unpaid (Internship) – No stipend
Location
Location Remote
Posted Date
Posted Date Today
Product research requirement gathering user story creation Agile methodology analytical thinking communication basic AI concepts SaaS fundamentals stakeholder management documentation
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Aptitude Practice Questions Open Resource ↗
Curated logical and quantitative problems to sharpen reasoning skills required for the first interview round.
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Company Interview Preparation Guide Open Resource ↗
Comprehensive guide covering typical interview formats, common product and technical questions, and tips to present yourself effectively.
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Comprehensive Interview Prep Resource Open Resource ↗
Extensive collection of interview experiences, mock questions and answer frameworks useful for product and HR rounds.
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Algorithm Practice Problems Open Resource ↗
A wide range of coding challenges to reinforce problem‑solving abilities, useful for technical discussions and case studies.

• Currently pursuing or recently completed a Bachelor’s or Master’s degree in Computer Science, Information Technology, Business Administration, Engineering or a related discipline.\n• Minimum aggregate of 60% (or CGPA 6.0/10) in the qualifying degree.\n• No active backlogs at the time of application.\n• Strong analytical, communication and problem‑solving abilities.\n• Passion for AI, cloud technologies and product development.\n• Open to learning quickly and taking ownership of deliverables.

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Round 1: Aptitude & Logical Reasoning Test
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Round 2: Technical/Product Discussion (product discovery, case studies, problem‑solving)
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Round 3: HR Interview (culture fit, motivation, career goals)
ProArch is a globally recognised software development and consultancy firm that specialises in cloud, data, artificial intelligence and digital transformation solutions. With delivery centres across multiple continents, ProArch helps Fortune‑500 enterprises modernise their IT landscape, migrate to the cloud and harness data‑driven insights. The company’s culture is built around continuous learning, collaborative problem‑solving and a strong focus on delivering measurable business value.\n\nProArch’s newest venture, Vector, is an AI‑native enterprise platform that aims to transform how organisations manage and optimise their cloud operations. Vector’s Six Intelligence Model – Reactive, Proactive, Predictive, Prescriptive, Reflective and Adaptive – enables customers to move from simple query‑answering to autonomous, self‑optimising cloud environments. The platform integrates with Microsoft Teams and a web portal to surface insights, recommendations and automated actions directly within the workflows of cloud service providers (CSPs) and managed service providers (MSPs).\n\nThe role is a structured three‑month unpaid internship that can evolve into a one‑year full‑time trainee programme, ultimately leading to a Software Engineer or Product Engineer position. Interns will work side‑by‑side with senior product managers, architects and engineers to translate complex cloud‑operations challenges into tangible product experiences. The focus is on product discovery, requirement definition, user‑experience design and analytics – all within an Agile, AI‑first environment.\n\nKey Responsibilities:\n1. Conduct deep‑dive product research to uncover customer pain points, personas and workflow gaps.\n2. Map identified use‑cases to the Six Intelligence Model and propose how each intelligence layer should be surfaced to users.\n3. Draft detailed product requirements, user stories, acceptance criteria and journey maps for engineering hand‑off.\n4. Collaborate with UI/UX designers to create wireframes and prototypes for Microsoft Teams and web‑portal experiences.\n5. Define and track product‑level metrics such as adoption rates, usage frequency and recommendation effectiveness.\n6. Analyse usage data to surface insights that inform iterative product improvements.\n7. Participate in sprint planning, backlog grooming and daily stand‑ups with cross‑functional teams.\n8. Prepare clear documentation and presentations for internal stakeholders and potential customers.\n9. Stay abreast of emerging AI, cloud and SaaS trends to inject innovative ideas into the product roadmap.\n10. Support the creation of demo environments and assist in customer proof‑of‑concept sessions.\n\nTech Stack & Tools: The internship will expose you to cloud platforms (AWS, Azure), AI/ML services, product management tools (Jira, Confluence), design tools (Figma, Sketch) and data‑visualisation libraries. While coding is not a primary focus, familiarity with Python or JavaScript is advantageous.\n\nGrowth Path: High‑performing interns may be offered a full‑time Trainee role, progressing to Associate Product Engineer, then Product Engineer and eventually Senior Product Manager or Technical Lead, depending on skill development and business needs.\n\nWhy Join Vector? You will work on a cutting‑edge AI‑native product that solves real‑world cloud‑operations problems for global enterprises. The mentorship from seasoned product and architecture leaders, exposure to Agentic AI concepts and the chance to influence a product from inception to market launch make this internship a unique launchpad for a career in enterprise SaaS product management.

Proarch — 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 🎯
Proarch Interview Preparation Corner

Comprehensive guide covering typical interview formats, common questions, and preparation tips for Proarch 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 (Product research, requirement gathering, user story creation, Agile methodology, analytical thinking, communication, basic AI concepts, SaaS fundamentals, stakeholder management, documentation) & 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
Proarch 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 Proarch as a Software Engineer / Product Role?
Preparation Tip: Highlight Proarch's market reputation, recent tech innovations, and how your skills in Product research 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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