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Software Engineer II Interview Questions

Practice 9403 coding, system design and machine learning questions from 546 companies, sorted by role, topic and interview round. Every question has step-by-step hints, a code runner that supports 8 languages and an AI mentor; members also get the full solution walkthrough.

9403
Questions
546
Companies
11
Topics
8
Languages

Showing 1–12 of 12 results

  • J.P. MorganMediumSoftware Engineer II
    Design Secure Token Authorization and Large-File Transfer

    Design a secure, enterprise-grade file transfer service that supports resumable multi-gigabyte uploads/downloads alongside fine-grained, token-based authorization and key management.

    System DesignOnsitesystem-designsecuritydistributed-systems
  • J.P. MorganMediumSoftware Engineer II
    Design a Multimodal Retrieval-Augmented Generation System

    This problem tests the ability to design an end-to-end RAG system capable of processing both text and image inputs while ensuring high retrieval precision, security, and traceability.

    ML System DesignOnsiteRAGMultimodalSystem Design
  • J.P. MorganMediumSoftware Engineer II
    Distinguish AI Skills, Agents, LangChain, and LangGraph

    This question tests the architectural understanding of modern LLM-based application frameworks and the distinctions between modular AI components, task-oriented agents, and multi-agent coordination systems.

    ML System DesignOnsiteLLMOrchestrationAgentic-Workflows
  • J.P. MorganMediumSoftware Engineer II
    Explain Python Concurrency, HTTP Update Semantics, Garbage Collection, and Deadlocks

    Assess core backend engineering fundamentals including Python concurrency tradeoffs, RESTful update semantics, runtime garbage collection mechanisms, and deadlock prevention strategies.

    Software Engineering FundamentalsOnsitepythonconcurrencyrest-api
  • J.P. MorganMediumSoftware Engineer II
    Explain Stack Use Cases and Mutability in Python Containers

    This problem tests the understanding of LIFO data structure applications, the implications of object mutability in Python, and the technical constraints imposed by hashability in container types.

    Software Engineering FundamentalsOnsitePythonData StructuresMemory Management
  • J.P. MorganMediumSoftware Engineer II
    Explain Why You Are Changing Jobs and How You Communicated the Decision

    This question assesses the candidate's ability to articulate professional motivations for moving roles while maintaining a positive narrative about their current employer and handling transitions with professional integrity.

    Behavioral & LeadershipOnsiteCommunicationCareer GrowthProfessionalism
  • J.P. MorganMediumSoftware Engineer II
    Explain a Project Architecture End to End

    Tests your ability to present a production system architecture end-to-end, detailing data flow, ownership boundaries, database indexing and partitioning strategies, resilience patterns, and concrete architectural trade-offs.

    System DesignOnsiteDatabase OptimizationArchitectureData Modeling
  • J.P. MorganMediumSoftware Engineer II
    Find the Maximum-Sum Contiguous Subarray

    Implement Kadane's algorithm to find the maximum sum of a non-empty contiguous subarray in linear time and constant auxiliary space, with proper handling for all-negative inputs and potential 64-bit integer overflow.

    Coding & AlgorithmsOnsitedynamic-programmingarrayskadanes-algorithm
  • J.P. MorganMediumSoftware Engineer II
    Implement Merge Sort

    This problem tests your ability to implement the Divide and Conquer paradigm, specifically the recursive merge sort algorithm, while maintaining stability and managing auxiliary space.

    Coding & AlgorithmsOnsiteSortingDivide and ConquerRecursion
  • J.P. MorganMediumSoftware Engineer II
    Optimize User-and-Region Queries on a Million-Row Table

    Evaluate and design database access patterns, indexing strategies, and scaling techniques (partitioning, sharding, replication) for a financial user-profile system with high regional skew and frequent lookups.

    System DesignOnsiteDatabase OptimizationIndexingPartitioning
  • J.P. MorganMediumSoftware Engineer II
    Reason About Concurrency, CAP Trade-Offs, and Kubernetes Scaling

    This problem tests your understanding of fundamental concurrency concepts, distributed systems trade-offs under partition, and the practical application of Kubernetes scaling mechanisms in a high-throughput environment.

    Software Engineering FundamentalsOnsiteConcurrencyCAP TheoremKubernetes
  • J.P. MorganMediumSoftware Engineer II
    Return the K Largest Integers

    This problem tests the ability to efficiently find the k largest elements in an unsorted array using heap-based data structures to optimize for cases where k is significantly smaller than the input size.

    Coding & AlgorithmsOnsiteHeapSortingAlgorithms