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Define the architecture for a new generation of natural language reporting experiences — designing AI-native systems that let hundreds of thousands of advertisers ask questions in plain language and receive intelligent, actionable insights in real time. This is not incremental work; you'll own the technical vision for how natural language interfaces integrate with Amazon Ads' reporting platform, shaping the product for years to come. The Measurement and Data Science (MADS) Reporting Experience team is reinventing how advertisers understand and act on their campaign performance across Amazon Ads. You'll navigate deep ambiguity to design systems that are inventive, scalable, and simple — identifying the right problems to solve, decomposing highly complex challenges into elegant architectures, and driving technical decisions at the frontier of AI and user experience. You'll establish cross-team partnerships across Ads to deliver cohesive experiences, influence technical direction beyond your own team, set the engineering standard for operational excellence, and raise the technical bar across the organization. Key job responsibilities - Own the technical vision and architecture for natural language reporting experiences serving hundreds of thousands of advertisers, making complex systems simple and extensible - Lead the design and delivery of AI-native software in highly ambiguous problem spaces, writing critical-path code and making trade-offs that balance short-term delivery with long-term architectural health - Establish and drive technical partnerships with dependencies, influencing their technical direction to ensure cohesive, high-quality end-to-end experiences - Decompose large-scale, ambiguous initiatives into parallel workstreams and guide the team to deliver incrementally while maintaining architectural integrity - Proactively identify architecture deficiencies and bottlenecks, proposing and leading efforts to resolve them — including deprecating or rearchitecting existing systems when necessary - Define and drive engineering best practices, operational excellence, security, and quality across the team and adjacent teams - Mentor engineers, lead design reviews, and raise the technical bar, ensuring the team grows stronger and can operate independently of any single contributor - Influence team and organizational technical strategy by bringing clarity to complexity, guiding future technology choices, and building consensus across stakeholders
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.