AI Data Engineer job opportunity at MLabs.

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Date2026-02-10T10:47:13.665Z bot
MLabs AI Data Engineer
Experience: 5-years
Pattern: full-time
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Italy

Senior AI Data Engineer (Agentic Systems) Location:  USA / Europe / Israel - with a 5hour overlap with EST hours Compensation: $130K - $150K We build the technology that powers safer, more accessible financial markets. Our risk management systems, oracles, and AI models currently secure over $200 billion in assets across the world's largest decentralized protocols, having processed more than $5 trillion in transaction volume . We recently launched a pioneering Financial Intelligence Platform that transforms complex market data into actionable insights, bringing institutional-grade intelligence to every participant in the ecosystem. The Role: We are looking for a Senior AI Data Engineer to design and build the agentic systems powering our intelligence platform. You will work at the intersection of LLMs, financial data, and production infrastructure, creating intelligent agents that reason, plan, and execute across complex financial workflows. Responsibilities: Agentic Systems: Design and build single and multi-agent systems incorporating planning, memory, and tool use. Infrastructure: Build and operate MCP servers with secure schemas and permissions. Workflows: Develop sophisticated agentic workflows using LangGraph or equivalent frameworks. LLM Integration: Manage prompts, structured outputs, and tool calling via SDKs. Evaluation: Define and run LLM evaluation pipelines for quality, correctness, latency, cost, and regressions. Observability: Build reliability infrastructure, including logging, tracing, retries, and state management. Performance: Optimize performance and cost-efficiency from prototype to production. Mentorship: Establish agentic best practices and mentor junior engineers. We need an engineer who moves with precision and understands how to bridge the gap between AI research and production-grade financial software. Experience: 5+ years of software engineering, with at least 2+ years specifically building production-level AI/ML systems. Agentic Expertise: Hands-on experience with agentic architectures, tool calling, and LangGraph (or equivalent). Protocol Knowledge: Practical experience with Model Context Protocol (MCP) servers. Evaluation Skills: Demonstrated experience designing and operating LLM evaluation pipelines. Technical Stack: Strong Python proficiency and API design skills. Retrieval Systems: Familiarity with RAG pipelines, vector databases, and embedding-based retrieval. Preferred Qualifications: Prior experience with financial data, DeFi/Crypto, or quantitative analysis. Background in distributed systems or high-throughput data pipelines. Active contributions to open-source AI/ML projects.

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