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REQUIREMENT_ID_1546 • 3-DAY_ACTIVE_POLICY N

Generative AI Engineer

Company
Company Raju Tech India
Type
Opportunity Type Full-Time Job
Salary
Stipend / Salary 10-15 Lacs PA
Location
Location Hyderabad, India
Posted Date
Posted Date Yesterday
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Processing Artificial Intelligence Languages Orchestration Python Ml Process Generation
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Aptitude Practice Questions & Mock Tests Open Resource ↗
Curated logical, quantitative, and verbal reasoning problems for the initial online screening round.
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Company-Specific Interview Preparation Corner Open Resource ↗
Detailed interview experiences, exam formats, and previous test questions for Raju Tech India and tech roles.
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Technical Placement Cheat Sheets & Question Bank Open Resource ↗
High-yield coding cheat sheets, core CS fundamentals (OOP, DBMS, OS, Networks), and rapid revision guides.
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Algorithm, DSA & Live Code Debugger Practice Open Resource ↗
Hands-on problem sets to improve coding speed and step-by-step memory debugging.

Experience: 8-12 Yrs. Open to matching qualifications.

1
Online Assessment / Technical Interview Rounds / HR Review
About Wilotus Wilotus is the integrated project management and construction ERP platform unifying cost, schedule, commercial, field operations and compliance into one connected cloud environment. Built on 30+ years of real project controls and capital project delivery experience, Wilotus serves construction organisations across infrastructure, mining, oil and gas, buildings and industrial sectors. Role Purpose The Senior AI/ML Full Stack Developer is a critical strategic hire responsible for bringing artificial intelligenceand machine learning capabilities to the Wilotus platform. This senior individual contributor will architect, build, and deploy AI-powered features across 25+ construction ERP modules - including predictive cost forecasting, schedule risk analysis, intelligent document processing, AI-assisted compliance checking, and smart workflow automation. With 10+ years of total experience and a deep AI/ML background, this person will define Wilotus's AI roadmap and set the technical foundation for platform intelligence, working directly with the founders and the Technical Delivery Manager. Key Responsibilities Architect and build the AI/ML layer across the Wilotus platform, defining the technical strategy for AI integration across 25+ modules Design and implement AI-powered features: predictive cost and schedule analytics, risk scoring, anomaly detection, smart recommendations, and automated reporting Build end-to-end AI pipelines - from data ingestion and model training to API serving and frontend integration Integrate large language models (Claude, OpenAI GPT) for intelligent document processing, contract analysis, and natural language search across platform data Develop the OpenClaw automation framework - Wilotus's proprietary AI workflow engine for construction process automation Build and deploy machine learning models for construction-specific use cases: cost estimation, schedule prediction, resource optimisation, safety risk scoring Create RAG (Retrieval-Augmented Generation) systems for intelligent knowledge retrieval across project documents, drawings, and specifications Implement computer vision capabilities for site progress tracking, defect detection, and drawing analysis Design AI-assisted compliance engines that automatically validate project data against regulatory requirements and contractual obligations Build full-stack features with Java (Spring Boot) backend and Angular/React frontend to deliver AI insights through intuitive dashboards and visualisations Establish AI/ML best practices, model versioning, performance monitoring, and A/B testing frameworks Evaluate and recommend AI tools, services, and infrastructure (AWS SageMaker, Bedrock, vector databases) to support platform intelligence Mentor engineering team members on AI integration patterns and collaborate with domain experts to identify high-impact AI use cases Contribute to patent filings and intellectual property development around Wilotus AI innovations Required Qualifications B.Tech/B.E. or M.Tech/MS in Computer Science, AI/ML, Data Science, or related discipline 10+ years of total software engineering experience with minimum 4-6 years focused on AI/ML development Deep expertise in Python for AI/ML development (TensorFlow, PyTorch, scikit-learn, pandas, NumPy) Strong full-stack development skills - Java (Spring Boot) backend and Angular or React frontend Proven experience integrating LLMs and generative AI into production applications (OpenAI, Claude, Hugging Face) Hands-on experience building and deploying ML models in production environments Strong understanding of NLP, computer vision, time-series forecasting, and classification algorithms Experience with RAG architectures, vector databases (Pinecone, Weaviate, ChromaDB), and embedding models Proficiency in prompt engineering, fine-tuning, and LLM application development Experience with AWS cloud services (EC2, S3, RDS, Lambda, SageMaker, Bedrock) Strong API design skills - RESTful APIs, GraphQL, and microservices architecture Experience with databases (MySQL, MongoDB, PostgreSQL) and data pipeline design Excellent problem-solving, communication, and technical leadership skills Preferred Qualifications PhD or advanced research in AI/ML, NLP, or computer vision Experience building AI features for enterprise SaaS, ERP, or construction technology platforms Knowledge of construction industry workflows, project controls, and cost management Experience with MLOps tools (MLflow, Kubeflow, Weights & Biases) for model lifecycle management Published research or open-source contributions in AI/ML Experience with edge AI for mobile and field applications Knowledge of AI safety, responsible AI practices, and bias mitigation Experience with Kubernetes, Docker, and containerised ML workloads Familiarity with BI tools (Highcharts, D3.js, Tableau) for AI-driven dashboards Construction, mining, oil and gas, or infrastructure domain experience Wilotus Technology Stack Java (Spring Boot), Angular, React, Python, AWS (EC2, S3, RDS, Lambda, SageMaker, Bedrock), MySQL, MongoDB, OpenAI API, Claude API, Hugging Face, LangChain, RAG, Vector Databases, TensorFlow/PyTorch, GitHub, Jira, Jenkins, Docker Working Conditions Full-time, on-site at VIJAYA KRISHNA TOWERS, Madhava Reddy Colony, Gachibowli, Hyderabad, Telangana 500032. 3- month probation period Application: careers@wilotus.com

Raju Tech India — 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 🎯
Raju Tech India Interview Preparation Corner

Comprehensive guide covering typical interview formats, common questions, and preparation tips for Raju Tech India 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 (Processing, Artificial Intelligence, Languages, Orchestration, Python, Ml, Process, Generation) & 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
Raju Tech India 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 Raju Tech India as a Generative AI Engineer?
Preparation Tip: Highlight Raju Tech India's market reputation, recent tech innovations, and how your skills in Processing 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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