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Job Responsibilities Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or breakdown technical problemsCreates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systemsLeverages enterprise-authorized AI coding assist tools within the work environment to improve code quality, delivery speed, and productivity across complex deliverables (e.g., code generation/refactoring, unit test creation, documentation), while validating outputs through peer review, automated testing, and secure coding standards; contributes learnings and reusable patterns to improve broader team effectiveness. 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. Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code developmentGathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systemsProactively identifies hidden problems and patterns in data and uses these insights to drive improvements to coding hygiene and system architecture Required qualifications, capabilities, and skills Formal training or certification on software engineering concepts and 3+ years applied experience Hands-on practical experience in system design, application development, testing, and operational stabilityExperience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languagesHands-on experience using enterprise-authorized AI-assisted software development tools within the work environment (e.g., for coding, test creation, troubleshooting, or documentation) with demonstrated ability to critically evaluate, validate, and refine AI-generated outputs for correctness, performance, and security. Understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; ability to guide peers on safe and effective usage within team practices. Overall knowledge of the Software Development Life Cycle and applicability of it using ADLC (Agentic Driven Life Cycle)Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security Preferred qualifications, capabilities, and skills Hands-on Knowledge of data engineering practices to support AI model training and deployment, including hands-on experience with libraries such as TensorFlow, PyTorch, Scikit-learn, and Keras Exposure to cloud technologies - AWS .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.