N #2824
Applications open
Full-Time Job
Senior Lead Python Developer Mumbai Andheri East 5 days WFO
Intelli Search Services
About the role
Senior Lead
Python Developer Experience
12+ Years Exp Shift Timings 12Pm -9PM 5 days work from Office (Monday to Friday)
Job Summary
We are looking for a Senior Lead Python Developer with 12+ years of strong software development experience and hands-on expertise in Python. The ideal candidate should have proven experience in designing scalable applications, leading development teams, and working with modern cloud and AI technologies. Candidates should have basic to intermediate exposure to Artificial Intelligence (AI), Generative AI, or LLM-based applications and a strong willingness to expand their expertise in these areas.
Key Responsibilities
- Lead the design, development, and delivery of scalable Python applications and services.
- Provide technical leadership and mentoring to Python development teams.
- Design robust, maintainable, and high-performance software architectures.
- Develop REST APIs, microservices, and backend services using Python.
- Conduct code reviews and establish coding, testing, and development best practices.
- Collaborate with product managers, architects, DevOps, QA, and other engineering teams.
- Troubleshoot complex technical issues and drive root-cause resolution.
- Participate in architecture and technical design discussions.
- Ensure application security, performance, scalability, and reliability.
- Work with cloud platforms and modern DevOps practices.
- Contribute to AI/Generative AI initiatives, including LLM-based applications, AI-powered features, or automation solutions.
- Stay current with emerging Python, AI, Gen AI, and software engineering technologies.
Required Skills
- 10+ years of overall software development experience.
- Strong hands-on experience with Python .
- Excellent knowledge of Python frameworks such as FastAPI, Flask, or Django .
- Strong experience with REST APIs and microservices architecture .
- Good understanding of Object-Oriented Programming, design patterns, and SOLID principles .
- Experience with relational and/or NoSQL databases such as PostgreSQL, MySQL, MongoDB, or similar.
- Experience with Git and CI/CD practices.
- Strong understanding of software development lifecycle and Agile methodologies.
- Experience leading technical teams and mentoring developers.
- Good understanding of cloud platforms such as AWS, Azure, or GCP .
- AI / Generative AI Exposure Basic or hands-on exposure to one or more of the following: Generative AI and Large Language Models (LLMs).
- OpenAI, Azure OpenAI, Gemini, Claude, or similar LLM platforms.
- Prompt engineering and LLM API integration.
- RAG (Retrieval-Augmented Generation) concepts.
- Vector databases and embeddings.
- AI-powered applications or automation.
- Frameworks such as LangChain, LlamaIndex, or similar technologies.
Eligibility & process
Who can apply
Experience: 10-16 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 Intelli Search Services and tech roles.
Technical Placement 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
Intelli Search Services Interview Preparation Corner
Comprehensive guide covering typical interview formats, common questions, and preparation tips for Intelli Search Services 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 (Python Framework, Artificial Intelligence, Machine Learning, Microservices, Python, Restfull Api, Large Language Model, Django) & 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
Intelli Search Services 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 Intelli Search Services as a Senior Lead Python Developer Mumbai Andheri East 5 days WFO?
Highlight Intelli Search Services's market reputation, recent tech innovations, and how your skills in Python Framework directly solve their team's objectives.
Highlight Intelli Search Services's market reputation, recent tech innovations, and how your skills in Python Framework 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.
25-35 Lacs PA
Mumbai, India
Experience: 10-16 Yrs. Open to matching q…
