L #2979
Applications open
Full-Time Job
Java Full Stack (Java, ReactJS, AWS, and exposure to AI tools) Software Engineer II
JPMorganChase
About the role
Job Description
You're ready to gain the skills and experience needed to grow within your role and advance your career — and we have the perfect software engineering opportunity for you
As a Software Engineer II at JPMorganChase within the Corporate Technology Employee Platforms team, you are part of an agile team that works to enhance, design, and deliver the software components of the firm's state-of-the-art technology products in a secure, stable, and scalable way. As an emerging member of a software engineering team, you execute software solutions through the design, development, and technical troubleshooting of multiple components within a technical product, application, or system, while gaining the skills and experience needed to grow within your role.
Job Responsibilities
- Participates in, design and develop scalable and resilient systems using Java to contribute to continual, iterative improvements for product teams
- Leverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards
- Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems
- Produces or contributes to architecture and design artifacts for applications while ensuring design constraints are met by software code development
- Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
- Identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture
- Contributes to software engineering communities of practice and events that explore new and emerging technologies
- Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation
Required Qualifications, Capabilities, And Skills
- Formal training or certification on software engineering concepts and 2+ years applied experience
- Hands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, testing, troubleshooting, or documentation) with demonstrated ability to critically evaluate and validate AI-generated output
- Proficient in coding in Java, SpringBoot, ReactJS languages
- Exposure to AWS cloud technologies
- Prompt engineering and Co-pilot knowledge
- Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectation
- Understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
- Knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, etc.)
Preferred Qualifications, Capabilities, And Skills
- Exposure to AI technologies
ABOUT US
Eligibility & process
Who can apply
Employment type: Full-time
Skills & stack
Selection process
Details are shared by the recruiter after shortlisting.
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 JPMorganChase 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
JPMorganChase Interview Preparation Corner
Comprehensive guide covering typical interview formats, common questions, and preparation tips for JPMorganChase 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 (Java, React, Spring Boot, AWS, CI/CD, Microservices, REST APIs, Docker) & 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
JPMorganChase 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 JPMorganChase as a Java Full Stack (Java, ReactJS, AWS, and exposure to AI tools) Software Engineer II?
Highlight JPMorganChase's market reputation, recent tech innovations, and how your skills in Java directly solve their team's objectives.
Highlight JPMorganChase'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.
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.
Competitive Package
Bengaluru, India
Employment type: Full-time
