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Job purpose We are looking for an enthusiastic Software Engineer to help build modern applications, internal tools, and automation systems that increasingly leverage AI capabilities. You will work primarily as a software engineer — designing APIs, building services, improving system reliability — while also integrating AI models into real features that improve productivity and user experience. This role is ideal for someone who is strong in software engineering and excited to apply AI in practical, production‑ready ways. A successful candidate will develop and enhance a large-scale micro services system. Candidates should expect to work with other team members on designing and implementing core platform components. Candidates should also expect to create unit tests, automated functional tests and load tests for all micro services. Duties and responsibilities Design, build, and maintain backend services, APIs, and internal tools. Develop clean, maintainable, and well‑tested code in Python, Node.js/TypeScript, or Go. Work with databases, message queues, and cloud infrastructure. Participate in code reviews, architecture discussions, and sprint planning. Improve system reliability, performance, and observability. Help evaluate AI tools, libraries, and model options. Collaborate with senior engineers on prompt design and AI workflow improvements. Ensure AI usage follows basic governance and data‑handling guidelines. Work closely with product managers to translate requirements into technical solutions. Collaborate with AI engineers, architects, and DevOps teams. Contribute to documentation, internal knowledge sharing, and continuous improvement. Capabilities 2–5 years of experience in software engineering. Strong skills in Python , Node.js/TypeScript , or Go . Experience building APIs, microservices, or backend systems. Familiarity with relational and NoSQL databases. Understanding of cloud platforms (AWS/GCP/Azure) and CI/CD pipelines. Good debugging, testing, and problem‑solving skills. Experience with Message Broker systems (RabbitMQ, Kafka, Pub/Sub). Experience with containerization (Docker, Kubernetes). Experience calling LLM APIs (OpenAI, Anthropic, Google). Understanding of how to integrate AI features into applications. Curiosity and willingness to learn new technologies. Ability to break down problems and propose practical solutions. Comfortable working in a fast‑moving environment. Familiarity with RPA, automation, or workflow engines is a plus.
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.