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Senior AI Engineer ## Our stack You should be strong across most of this. - Agent frameworks: LangGraph / LangChain — building agents, subagents, and orchestrated subagent fleets. - Frontend: React, React Native. - Backend: Node.js. - Models (we're model-agnostic): Claude / Anthropic, OpenAI / Codex, DeepSeek, Gemini, Sakana — routing across multiple models per task. - Agent infrastructure: MCP servers, subagent orchestration, short-term and long-term memory systems. - Data: integrating external data sources into agents; synthesizing unstructured/structured data into models; scraping (bonus). - Domain (preferred): blockchain data, blockchain RPC, stablecoins. ## The role You'll lead the design and delivery of our most important consumer AI features — owning the architecture, quality, and roadmap of how AI shows up in the product. You'll set technical direction, mentor other engineers, and be the person who makes hard applied-AI problems ship reliably at scale. This is an applied product role, not a research or protocol-engineering role. ## What you'll do - Own end-to-end design and delivery of consumer-facing AI features, from concept to production. - Architect robust agent systems with LangGraph / LangChain : agents, subagents, and orchestrated subagent fleets. - Design and build MCP servers and the tooling that connects agents to the rest of the product. - Build short-term and long-term memory systems and integrate external data sources into the agent fleet. - Route intelligently across multiple AI models (Claude, OpenAI / Codex, DeepSeek, Gemini, Sakana) based on task, quality, latency, and cost. - Build the eval and observability foundations that let the team ship quality improvements with confidence. - Set technical direction for applied AI and mentor junior and mid-level engineers. - Partner with product and leadership to shape what we build and why. ## What we're looking for - 5+ years of software engineering experience, with a strong track record of shipping consumer-facing products to real users at scale. - Demonstrated experience building applied AI / LLM-powered features in production — not just experiments. - Deep fluency in TypeScript/Node.js and/or Python; experience with React and/or React Native. - Hands-on experience building agents and subagents , including subagent orchestration and MCP servers . - Experience working across multiple model providers and routing between them. - Experience integrating external data sources into agents for short-term and long-term memory . - Experience designing evals and improving model-driven systems with data. - Strong product instincts: you make good trade-offs between speed, quality, cost, and UX. - Ability to lead projects and level up the engineers around you. ## Nice to have - Strong at scraping unstructured data and turning it into something an agent can use. - Experience with blockchain data, blockchain RPC, and stablecoins . - Experience in crypto, fintech, or payments , ideally on consumer products. - Experience scaling AI features under real latency, reliability, and cost constraints. - History of taking 0→1 products to launch. As part of the screening process, please kindly include the following at the bottom of your resume/application: 1. Your top two favorite products 2. One of your favorite apps and one of your favorite brands, with a brief explanation of why you like them 3. A URL link to your portfolio Please note that applications with this information will be preferred over those without.
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.