N #2426
Applications open
Full-Time Job
Engineering Manager
Hilabs
About the role
Hiring: Engineering Manager | HiLabs | Bengaluru Company: HiLabs Job Title: Engineering Manager Location: Manyata Tech Park, Bengaluru Work Mode: Work from Office Experience: 10+ Years Industry: IT / Software Product Development Employment Type: Full-time About HiLabs HiLabs is a US-based healthcare technology company leveraging Artificial Intelligence (AI), Machine Learning (ML), and big data technologies to improve data quality in the US healthcare industry. Our core platform, MCheck, combines explainable AI with healthcare-specific business knowledge to help improve data quality and deliver innovative business solutions. Role Overview We are looking for a technically strong Engineering Manager with a proven career progression from software developer to technical leadership in fast-paced IT product companies. The ideal candidate will bring a strong combination of hands-on technical expertise, engineering execution, people management, and the ability to lead and scale high-performing engineering teams. Key Responsibilities Partner with business teams to understand requirements and deliver end-to-end technical solutions. Provide technical direction and expertise across system design, software development, and systems integration. Lead engineering teams to deliver projects within defined timelines and quality expectations. Coordinate resources, delegate responsibilities, and drive effective project execution. Make sound technical decisions and resolve complex engineering challenges. Plan team capacity, identify resource requirements, and improve development productivity. Recruit, mentor, manage, and develop engineering talent, including performance management. Build a collaborative engineering culture focused on innovation, quality, ownership, and continuous improvement. Communicate effectively with cross-functional teams and clients. Develop expertise in relevant product domains and drive engineering excellence. Required Skills and Qualifications Bachelor's degree in Computer Science, Engineering, or a related field. 10+ years of experience with a demonstrated progression from software development to technical leadership in product-based IT companies. Strong technical foundation combined with effective people management capabilities. Experience managing engineering teams of 10+ members, with the ability to lead larger teams. Strong knowledge of software design, development, and systems integration. Demonstrated experience in technical team building, recruitment, and performance management. Excellent communication, interpersonal, problem-solving, and decision-making skills. Ability to collaborate cross-functionally and drive engineering initiatives independently. Good to have: Experience in the healthcare or insurance domain. This is preferred but not mandatory. Why Join HiLabs? Opportunity to work on AI-driven healthcare technology solutions. Competitive compensation and comprehensive benefits. Medical coverage, employee stock options, and employee recognition programs. Collaborative work environment with opportunities for professional growth and career advancement. Interested candidates can apply
Eligibility & process
Who can apply
Experience: 8-13 Yrs. Open to matching qualifications.
Skills & stack
Selection process
- Online Assessment / Technical Interview Rounds / HR Review
Prep kit
19 resourcesStudy material 4
Aptitude Practice Questions & Mock Tests
Curated logical, quantitative, and verbal reasoning problems for the initial online screening round.
Company-Specific Interview Preparation Corner
Detailed interview experiences, exam formats, and previous test questions for Hilabs and tech roles.
Technical Placement Cheat Sheets & Question Bank
High-yield coding cheat sheets, core CS fundamentals (OOP, DBMS, OS, Networks), and rapid revision guides.
Algorithm, DSA & Live Code Debugger Practice
Hands-on problem sets to improve coding speed and step-by-step memory debugging.
Company-specific guides 4
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.
COMPANY GUIDE
Hilabs Interview Preparation Corner
Comprehensive guide covering typical interview formats, common questions, and preparation tips for Hilabs and off-campus tech roles.
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.
CODING PRACTICE
Algorithm and Data Structure Problem Set
Practice problems to improve coding proficiency and algorithm problem-solving speed for technical rounds.
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 (Engineering Management, Team Management, Project Management, Project, Team, Machine Learning, System Design) & 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
Hilabs 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 Hilabs as a Engineering Manager?
Highlight Hilabs's market reputation, recent tech innovations, and how your skills in Engineering Management directly solve their team's objectives.
Highlight Hilabs's market reputation, recent tech innovations, and how your skills in Engineering Management 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).
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.
Explain your prioritization strategy, proactive communication with mentors/peers, and agile mindset.