AI Data Engineer

🕒 April 6

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MLabs

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51 - 200 employees

MLabs Consulting helps to setup project specification, implementation, management and maintenance of technical projects for AI, Fintech, Information Technology and more. We specialise in functional programming, compilers, AI, DevOps and full-stack development.

📋 Description

• 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.

🎯 Requirements

• 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.

🏖️ Benefits

• Competitive Compensation & Equity: They offer a package aligned with growth, performance, and merit. • Professional Growth: Be a foundational member of a rapidly expanding, global technology company with significant room for career advancement. • High-Stakes Impact: Work on systems that secure hundreds of billions of dollars and define the future of financial risk management. • Talent-Dense Team: Collaborate with world-class data scientists and engineers in a high-performance culture.