Lead AI Engineer

Twelve Data is a financial market data platform. One API gives developers, fintechs, and trading teams real-time and historical data across stocks, forex, crypto, ETFs, indices, and fundamentals, over REST and WebSocket. We cover 50+ exchanges and process about 1 billion requests a day. Over 70,000 active users rely on us. Most find us, sign up, and start building without ever talking to sales, so the product does the selling: fast, reliable data, clear docs, and pricing that makes sense. The team comes from quantitative trading and AI/ML. We're bootstrapped and self-funded, with no investors setting the pace. We're a distributed team of 20. Everyone owns real parts of the product, and the work you ship reaches users the same week. We are opening a hub in Dubai and are actively hiring for it. This role is based in our Dubai hub, where the founder and core team will work. We are looking for a senior engineer who writes code together with AI and makes the whole team faster. You will not only work fast yourself, but also find, verify, and implement AI practices that save hours, reduce defects, and speed up feature delivery. You will be the first engineer to systematically work on AI in the company. This is a rare opportunity to set the direction from scratch and build practices the way you see fit. There is a team nearby that will support you. We move fast. People work hard because they see the result and influence the product directly. Morning spec, evening solution in production. That does not mean we skip tests and review: we have mandatory code review, quality standards, and on-call rotations that keep reliability high. Without unnecessary bureaucracy. And yes if a new model drops overnight, we expect you to master it by morning and make it useful for Twelve Data by evening. (Sleep is optional; shipping is not :)) What tasks await you Development with AI tools You will write code, tests, documentation, migrations, and prototypes paired with AI. You will own a feature from idea to production, independently find edge cases, verify AI results, and prevent errors and vulnerabilities from reaching production. Your code will go through mandatory deep review by senior engineers. Advancing AI practices in the team You will systematically research, test, and implement AI tools and agents: code review, test generation, documentation, RAG, CI/CD automation, codebase analysis. You will build custom agents on top of corporate Claude and other models, create internal guidelines and guardrails, and train the team through hands-on sessions and demos. A solution that proves effective you can propose to the CTO for adoption across the entire engineering team. Twelve Data presence for AI agents You will be responsible for making our data and products accessible to AI agents and the ecosystem around them. That means publishing integrations, apps, and supporting protocols through which agents can access our data. This is a new direction, and you will shape it from scratch. Working with code and infrastructure You will work with high-load architecture, microservices, PostgreSQL, and GitLab CI/CD. You will find bottlenecks in code and infrastructure, fix logic errors. You will ensure reliability and observability for systems that process hundreds of millions of requests per day. We expect that you Technical skills • Have a senior level or above, 5+ years of experience • Are confident with Go and Python • Know PostgreSQL deeply: schema design, query optimization, transactional integrity • Have worked with high-load systems and big data pipelines • Are proficient with Docker, Redis, Kafka, gRPC, REST • Have hands-on experience with GitLab CI/CD and trunk-based development • Understand microservice architecture, distributed systems, APIs • Can quickly analyze foreign code and identify architectural risks • Are confident with AI tools: Claude, Cursor, etc. • Have experience building custom AI agents • Can craft prompts and manage context: multi-layered instructions, system context, iterative refinement • Know how to measure AI output quality • Are attentive to numbers, transactions, and data integrity • Have a proven ability to rapidly review extensive technical documentation and efficiently spot discrepancies with requirements and suboptimal solutions Soft skills • Take ownership: you don't wait for instructions, you see a problem and fix it, you act like an owner of the product • Don't outsource thinking to AI:you know what you want and use AI as a tool, not as a replacement for judgment • Are autonomous: you drive tasks from zero without excessive supervision • Work well in a team without conflicts, own the task, and act as a reliable partner • Can explain complex things in simple language: to colleagues, leadership, users Nice to have • Experience in fintech, knowledge of PCI DSS, PII, regulatory requirements • Deployed LLMs on your own servers (vLLM, SGLang, Ollama) • Worked with vector databases (pgvector, Qdrant, Weaviate) • Worked with Terraform or Ansible • Worked with ClickHouse, Cassandra, ScyllaDB, TimescaleDB • Trained teams and ran internal hands-on sessions • Understand markets: stocks, forex, crypto, ETFs • Have published integrations, apps, or tools for AI agents