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As a Pirate We’re not looking for a software engineer who works through tickets. We’re looking for someone who can identify, board, and take over a merchant vessel in record time, and who leaves behind a ship where every knot is flawless. AI now handles much of the design, prototyping, and coding. What matters is building fast without leaving chaos behind. Concretely: Design thinking — you understand the actual problem before writing a single line of code Rapid prototyping with AI — you don’t treat modern AI tools as a novelty but as a core part of your workflow, going from idea to working prototype in hours instead of weeks Agentic coding with a firm hand — you let agents code for you, but you keep them on a short leash: strict architecture guidelines, clean design patterns, no sprawl Speed with foresight — you build fast, but you’re already thinking two releases ahead. Every important design decision is documented and traceable, even when you built at sprint speed As an Architect Once the vessel is taken, you take command. Now structure matters more than speed. Software & feature blueprinting — the plan exists before the building starts Systems engineering — you think in systems, not isolated components Software engineering design patterns — core toolkit, not bonus knowledge Architecture design — you make and own the big decisions, and you know when a microservice earns its keep and when it's just overhead Cloud-native product architecture — you design products for the cloud, not applications that happen to run there Code reviews — held to a high standard, but constructive Extreme attention to structure — loose ends are not a minor offense to you Broad foundation across databases, data structures, storage, cloud functions, and infrastructure as code — you choose deliberately, not out of habit Tasks The work itself, concretely: Building and maintaining AI agentic workflows — on industry-standard frameworks, with the same architectural discipline you would apply to any other production system Building and maintaining data processing pipelines — ingestion, transformation and enrichment of customer data: reliable, observable, and safe to reprocess Shipping features end to end — the React screen, the Python service behind it, and the AWS infrastructure it runs on Making quality measurable — evaluation sets, tracing, and budgets for latency and cost, so a regression is caught by us and not by a customer Integrating with our customers’ systems — real business data from real enterprise landscapes, rarely clean and never twice the same Requirements Multiple years of experience as a software engineer, ideally with ownership of architecture decisions Practical, current experience with AI-assisted development (not just “tried it once”) Understanding of cloud native architecture, ideally on AWS End-to-end reach — ideally you are at home in the frontend, the backend and the infrastructure, and can take a feature all the way to production without handing it over at every boundary The rare combination: high speed AND high structural discipline Strong communication skills to explain and defend architecture decisions — including to agents that “wanted to solve it differently” Benefits ✨ Shape and own the technical architecture as the company scales ✨ Work within a modern, AI-driven engineering setup ✨ High level of autonomy and real impact from day one ✨ Dynamic, entrepreneurial environment with room to grow Send us resume / portfolio / GitHub / an example of a project you recently built using an AI-assisted workflow No cover letter needed. Just show us you can board and clean up.
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.