Senior Applied AI Engineer

This is a fully remote position, open to applicants in Europe.

📋 Description

• Develop AI agents and agentic workflows from the ground up, which includes agent loops, tool-calling, structured outputs, planning and state management, retries, guardrails, and orchestration/harness layers.

• Integrate large language models through provider APIs such as Anthropic, OpenAI, open-weight models, and MCP.

• Deliver internal AI automations that minimize engineering, support, and growth-related tasks.

• Automate engineering workflows and pull-request reviews across platforms like GitHub, Slack, Intercom, and Jira.

• Create support deflection and social/market-listening automations.

• Develop tailored in-product AI features for the trading terminal and enhance the developer experience in collaboration with Product and Core Platform Engineering teams.

• Prototype and transition AI capabilities to production with the platform team.

• Make informed buy-vs-build decisions for AI solutions.

• Implement evaluation, observability, and cost control measures for every system deployed.

• Function within SOC 2 / ISO-track security and AI governance standards.

• Manage source code, customer data, and product data with integrity.

• Write and maintain production code, working independently within a streamlined team.

• Report directly to the COO and collaborate with the CTO, Head of Product, and Head of IT & Security.

• Provide reliable, measurable AI systems in production that offer time savings or product enhancements.

⛳️ Requirements

• Over 8 years of experience in production software engineering.

• Extensive expertise with APIs, integrations, and systems, including REST, webhooks, OAuth, event-driven systems, and distributed architectures.

• Complete ownership of production integrations from start to finish.

• 2–3+ years of experience in building and deploying production LLM/agent systems from scratch using provider APIs.

• Personal experience in crafting agent loops, orchestration/harness layers, tool-calling, structured outputs, guardrails, and RAG for real-world users.

• Proficient in Python and TypeScript.

• Solid experience in production software engineering and code ownership; advisory or no-code/low-code experience is not sufficient.

• Familiarity with evaluation and observability, including golden datasets, evaluation harnesses, tracing, and cost/latency guardrails.

• In-depth knowledge of Anthropic, OpenAI, open-weight LLM APIs, MCP, and agent frameworks.

• Competence in using AI coding tools such as Claude Code and Cursor.

• Experience with AWS and/or DigitalOcean, Docker, CI/CD, SQL, and Postgres.

• Strong judgment in buy-vs-build decisions and maturity in security/data governance.

• Capability to handle production and customer data responsibly.

• High level of autonomy in a lean team environment.

• Availability in the EU/UK timezone with significant overlap with Central European working hours.

• Proficiency in Go is a significant advantage.

• Experience in fintech, trading, or market-data domains, or genuine experience as a user of trading platforms is a plus.

• Contributions to AI tooling in open-source projects such as LangChain, LlamaIndex, vLLM, or DSPy are advantageous.

• Experience with production RAG and vector databases is a plus.

• Background in code-generation, transpilation, or developer-experience tooling is a bonus.

• Previous experience in forward-deployed, applied-AI, or internal-enablement engineering is a plus.

🏝️ Benefits

• Fully remote work arrangement.

• Employment through an Employer-of-Record in the candidate's home country.

• Light travel with occasional team and leadership meetups.