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Join us as a Software Engineer to build the AI execution layer where go-to-market agents do the work, not just answer questions. Taizen builds purpose-built AI agents for Product Marketing, Sales Enablement, and Revenue teams. Our AI agents connect to tools like Gong, Salesforce, HubSpot, and Slack, then proactively run recurring workflows without waiting to be prompted. 📍 Barcelona, in-person at least 4 days/week. At our size, being in the room means you're next to the founders, the technical team and the roadmap. 💰 €40k–€65k + equity. Why take the bet We're early-stage, so the risk is real: timelines move, and equity is worth what the company becomes, not what it's valued at today. Here's why we think it's worth it. We're two ex-Spotify engineers who've shipped and scaled software used by millions, funded, and building with real customers every week. We move fast and we break things, but we also run SOC2 and ISO 27001-compliant infrastructure, a combination you won't find in most pre-seed teams. There's also a shift worth betting on. Agents can write boilerplate and wire up endpoints faster than any human now. What they can't do is untangle a vague problem, design a data model that holds up under real usage, or debug something failing in a way nobody expected. That's what we're hiring for. After a few years in the job, the thing that sets you apart isn't how fast you type, it's your judgment, and that's exactly what this role leans on. What we do Go-to-market teams are drowning in signals they can't act on fast enough. Competitor moves, deal objections, buyer feedback, and coaching gaps are trapped across call recordings, CRM notes, documents, and Slack threads. We're building agents that do the operational work: Competitive intelligence: Monitor competitor activity and calls, then deliver reports, updated battlecards, and rep talk tracks automatically Deal and account intelligence: Show sales leaders where deals are advancing or stalling, while helping BDRs research territories and identify the right accounts to bring into pipeline AI roleplay: Let reps practise against voice-based AI buyers grounded in real deals, objections, and battlecard content AI Win/loss interviews: Interview buyers after a deal and turn the conversations into structured insights without someone scheduling every call The Stack You won't just work inside this stack, you'll help decide where it goes. How our retrieval layer evolves as we grow past our first customers is still an open question you'd have a say in. Frontend: React Backend: two services, a Node/TypeScript core and a Python agent service Retrieval: our own vector store written in Rust, SOTA late-interaction retrieval Data: Postgres + MongoDB Agents: our own harness, not an off-the-shelf framework, and model-agnostic ML: a mix of our own and open-source models; Modal for GPU work Infra: AWS (RDS, EC2, CloudFront, S3, ECR, ECS, ElastiCache, Lambda), MongoDB Atlas, Grafana + Prometheus, GitHub Actions What you'll do Ship features end-to-end, from customer problem to design, deployment, and iteration — architecture decisions included Build reliable backend services and workflows behind the agents Build product surfaces across the web app and Slack Work on data models and infrastructure that handle very different data types, tuned for fast reads and writes Own quality: testing, monitoring, observability, and incident response Keep the delivery pipeline healthy: CI/CD, deployments, and infrastructure hygiene What we're looking for CS degree, Bachelor's or Master's, or equivalent 4+ years shipping production software on a product team where you've owned something. Side projects are a bonus and can compensate for lack of experience Strong problem-solving and solid CS fundamentals, which matter to us more than your framework list or years on the clock Comfortable with TypeScript/React and Python/Node, or quick to pick them up Some hands-on time with CI/CD, deployments, and observability, and up for owning more here High agency and happy working on a small, cross-functional team Nice to haves Shipped features with LLM or AI components Curious about information retrieval or distributed systems — a bonus, not a requirement Built integrations with third-party APIs Pick up new tools and languages fast Why you'll like it here 🚀 We are growing fast 💻 You get to choose your own machine and peripherals 💰 Almost unlimited token budget 🏗️ Real architecture ownership you wouldn't touch for years at a bigger company 🤖 A new kind of product: AI-native and agent-powered, not a chatbot wrapper 🥳 We work hard and celebrate the wins, small and big 🎉 Offsites a few times a year to work and play together
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.