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Responsibilities (Outcomes & Ownership) Build and operate scalable, secure, and high-performing systems for Avalara's global platform, ensuring strong reliability, observability, and performance at scale Drive engineering velocity and quality by embedding AI into development workflows (coding, testing, design, documentation) and strengthening CI/CD practices Design and deliver AI-enabled product capabilities that improve automation, data processing, and measurable customer outcomes Lead technical design and architectural decisions for complex distributed systems, balancing scalability, cost, and reliability Reduce production issues through proactive system design, improved architecture, and strong operational practices Demonstrate and drive measurable impact from AI (e.g., improved speed, quality, automation), while ensuring responsible, secure, and well-governed AI adoption across engineering and product development . Required Qualifications Bachelors in Computer Science/Engineering with 8+ years of building and owning scalable, distributed systems at a senior level. Strong hands-on experience with .NET (C#) / JAVA / Python and React (TypeScript), including designing and operating APIs (REST/GraphQL) in cloud-native environments (AWS), with Infrastructure as Code (Terraform), CI/CD pipelines, and containerization (Docker/Kubernetes). Solid understanding of databases (relational/NoSQL) and automated testing strategies across the development lifecycle. Demonstrated hands-on use of AI with measurable impact on engineering or business outcomes, with the ability to apply it responsibly and effectively. Experience working on SaaS or enterprise-scale platforms, ideally within compliance, financial, or other regulated domains, and leading cross-team technical initiatives Strong English communication skills, with the ability to collaborate across global teams, influence decisions, and drive alignment.
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.