AI Data Infrastructure Engineer
Location: Palo Alto, CA
Department: Business Development
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Automatically discovering new data sources across the internet
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Using LLMs and agents to evaluate and filter data sources at scale
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Building systems that significantly increase data throughput without increasing headcount
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This role sits at the intersection of data engineering, LLM systems, and applied AI infrastructure, and is ideal for someone who enjoys building from scratch and shipping fast.
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Build LLM-powered agents and automation systems for data discovery and evaluation
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Design and implement data pipelines for ingesting, filtering, and transforming large-scale datasets
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Develop internal tools for data quality scoring, ranking, and selection
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Experiment with scraping, APIs, and programmatic data collection at scale
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Rapidly prototype and iterate on systems that improve data acquisition speed and quality
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Collaborate closely with Data Engineering and Research teams to align data systems with model needs
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Build scalable systems that increase data throughput and efficiency
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Strong technical foundation (engineering, scripting, systems, or data-focused background)
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Experience building tools, automation, or pipelines from 0→1
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Comfortable with Python, APIs, scraping, or backend workflows
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Interest in LLMs, agents, or applied AI systems
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Strong problem-solving ability and a builder mindset
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Ability to operate independently in fast-paced, ambiguous environments
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Experience with LLM frameworks or agent systems
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Experience with large-scale data processing or distributed systems
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Familiarity with automation tools, workflow builders, or AI-assisted development (e.g., Cursor)
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Startup or high-growth environment experience
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