Technical Fundamentals & Core Skills Topics
Core technical concepts including algorithms, data structures, statistics, cryptography, and hardware-software integration. Covers foundational knowledge required for technical roles and advanced technical depth.
Cryptography and Encryption Fundamentals
Comprehensive understanding of modern cryptography and encryption principles used to build secure systems. Candidates should be able to explain the differences between symmetric and asymmetric encryption, appropriate use cases for each, and common algorithms by full name such as Advanced Encryption Standard and Data Encryption Standard for symmetric ciphers and Rivest Shamir Adleman and elliptic curve based algorithms such as Elliptic Curve Digital Signature Algorithm and Elliptic Curve Diffie Hellman for public key operations. Describe hybrid encryption patterns in which asymmetric cryptography is used to protect a symmetric session key, and discuss block cipher modes of operation including cipher block chaining and authenticated encryption modes such as Galois Counter Mode, as well as the role of initialization vectors and nonces. Cover hash functions and integrity checks with properties such as collision resistance and preimage resistance, message authentication codes, authenticated encryption, and digital signatures for authentication and nonrepudiation. Include high level Public Key Infrastructure concepts including certificates and certificate authorities and how certificates are used to establish trust, together with foundational Transport Layer Security and Secure Sockets Layer principles without requiring deep certificate lifecycle management knowledge. Emphasize key management and operational concerns including secure key generation, secure storage, rotation and compromise handling, randomness and entropy sources, recommended key lengths and algorithm lifecycle considerations, and performance and scalability trade offs. Be prepared to discuss common implementation pitfalls and failures such as weak key sizes, poor random number generation, improper key reuse, and lack of authenticated encryption, plus threat models and practical applications including encrypting data at rest and in transit, secure channels, and signing and verification. Avoid deep mathematical proofs unless specifically requested, but be ready to reason about practical trade offs, algorithm selection, and secure implementation patterns.
Technical Depth and Domain Expertise
Covers a candidate's deep, hands-on technical knowledge and practical expertise in their own specialization and their ability to provide credible technical oversight in that area. Interviewers probe the specific patterns, internals, and constraints of the candidate's domain and how the candidate stays current in the field. The concrete sub-areas vary by specialization: for platform, infrastructure, or backend-systems roles this might mean OS internals (Linux and Windows), networking fundamentals (transport and internet protocols, DNS, routing, firewalls), database internals and performance tuning, storage and I/O behavior, virtualization and containerization, or cloud infrastructure and services; for data, ML, or AI roles this might mean model architectures and training dynamics, distributed training and serving internals, feature and data-pipeline design, or statistical methodology; for other technical specializations (sales engineering, technical support, IT business analysis, and similar) this means the specific systems, tools, and technical trade-offs central to that role's own domain. Regardless of domain, candidates should be prepared to explain architecture and design trade-offs, justify technical decisions with metrics and benchmarks, walk through root cause analysis and debugging steps, describe tooling and automation used for deployment and operations, and discuss capacity planning and scaling strategies relevant to their field. For senior candidates, expect both breadth across adjacent areas and depth in one or two specialized areas, with concrete examples of diagnostics, performance tuning, incident response, and technical leadership. Interviewers may also ask why the candidate specialized, how they built that expertise, how it shaped real technical decisions and trade-offs, expected failure modes and performance considerations, and how the candidate mentors others or drives best practices within their specialization.
Problem Solving and Scenario Analysis
Candidates are expected to demonstrate a systematic, structured approach to analyzing and resolving complex scenarios relevant to their field. This includes clarifying the problem statement, eliciting requirements, constraints, and assumptions, and identifying missing information or ambiguous areas. Candidates should decompose complex problems into logical components, prioritize tasks or evidence, generate multiple solution options, and perform trade-off evaluation that balances impact, feasibility, cost, and risk. Core skills assessed include root cause analysis, structured diagnosis of an incident or issue, and reasoning through realistic scenarios drawn from the candidate's own domain (for example, a technical migration, a process breakdown, a customer escalation, a resourcing conflict, or a policy decision). Candidates should define how they would validate a proposed solution (test cases, acceptance criteria, or success metrics), describe how they would monitor or verify the outcome after implementation, and identify opportunities for improvement, risk mitigation, or automation where applicable. Clear communication of the recommended approach, the expected outcomes, and the rationale behind trade-offs made is essential.
Linux System Administration Fundamentals
Core Linux administration knowledge and hands on operational skills required to install, configure, and maintain Linux systems. Covers user and group management, file permissions and ownership, process management and signals, package management across distributions, the boot process and runlevels or targets, basic systemd service control, filesystem navigation and basic disk management, common system configuration files, shell and command line proficiency, and differences between major enterprise and community distributions. Candidates should demonstrate practical troubleshooting of routine issues, patching and updates, and an ability to perform day to day administration tasks reliably.
OSI Model and TCP IP Stack
Comprehensive knowledge of the seven layer Open Systems Interconnection model, including Layer One Physical, Layer Two Data Link, Layer Three Network, Layer Four Transport, Layer Five Session, Layer Six Presentation, and Layer Seven Application. Understand the primary responsibilities and services at each layer, how data is packaged and transformed as it moves down and up the stack through encapsulation and decapsulation, and the unit of data at each stage such as bits at the physical layer, frames at the data link layer, packets at the network layer, and segments at the transport layer. Be able to identify common protocols and services that operate at each layer, for example Ethernet and link layer protocols at the data link layer, Internet Protocol at the network layer, Transmission Control Protocol and User Datagram Protocol at the transport layer, and application layer protocols such as Hypertext Transfer Protocol and Domain Name System at the application layer. Understand which hardware devices operate at which layers, such as cabling and transceivers at the physical layer, switches and bridges at the data link layer, and routers at the network layer, and how these devices affect forwarding and inspection. Know how the Open Systems Interconnection model maps to and differs from the four layer Transmission Control Protocol and Internet Protocol stack, including which functions are combined or abstracted differently, and how layering choices affect security placement, encryption strategy, performance, and troubleshooting. Be able to apply this knowledge to diagnose faults by mapping symptoms to layer specific causes and to reason about header fields, addressing and port schemes, segmentation and retransmission behavior, and cross layer interactions.
Trees & Graphs Basics
Understand binary trees, binary search trees, and basic graph concepts. Know tree traversal methods: in-order, pre-order, post-order, and level-order (BFS). Practice DFS and BFS implementations. Know the difference between directed and undirected graphs. Solve medium-difficulty tree and graph problems.
Certifications and Technical Foundation
Focuses on a candidate's formal qualifications and foundational hands on technical skills. Topics include professional certifications, coursework, and practical lab experience in networking, systems, and relevant toolsets; honest assessment of strengths and learning gaps; examples of hands on exercises or projects that demonstrate core competencies; and plans for continuing technical development. Interviewers will use this to gauge baseline technical literacy and fit for role expectations.
Technical Depth and Current Knowledge
Assessment of how deep a candidate's technical expertise actually runs in their own domain, and how current that knowledge is with today's tools, systems, and practices. Interviewers probe for genuine hands-on depth versus surface familiarity: candidates should be able to explain the core mechanisms behind the systems and tools they work with, articulate concrete trade-offs between competing technical approaches, walk through how they debug or troubleshoot problems in their area, describe how they research and validate unfamiliar topics before relying on them, and give real examples of technical decisions they have owned along with the reasoning behind those decisions. This includes maintaining rigorous technical fluency even in roles that have moved away from daily hands-on work (for example engineering leadership, technical sales, or technical program management), where interviewers may probe whether the candidate can still reason precisely about the underlying systems they oversee, sell, or coordinate.
Graph Algorithms and Routing
Model spatial and network problems as graphs and apply algorithmic techniques used in routing, batching, and location optimization. Expect to reason about shortest path algorithms such as Dijkstra and A Star, breadth first search and depth first search, union find for connectivity, minimum spanning trees, and flow algorithms for capacity constrained routing. Discuss complexity analysis, data structures for efficient graph traversal, heuristics and approximations for vehicle routing and order batching, time window and capacity constraints, and approaches to handle dynamic updates and large scale graphs in streaming or incremental environments.