Superside - Staff AI/Data Engineer
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Requirements
• 8+ years in high-performance engineering environments — ideally at companies pushing the frontier of enterprise AI, legal AI, or knowledge-intensive agent systems. • Proven experience building agentic workflows and RAG systems in production, with a focus on making AI output trustworthy and reliable — not just functional. • Deep understanding of how language models represent and use knowledge, well beyond prompt engineering or standard retrieval patterns. You've thought seriously about memory architectures, reasoning under uncertainty, and dynamic retrieval. • Experience with LangChain or LangGraph (or equivalent) for building multi-agent systems; strong Python skills, ideally with FastAPI. • Hands-on experience with a major cloud data platform — Snowflake, BigQuery, or Databricks — and comfort designing architectures that handle large data volumes reliably. • Strong opinions about where current AI approaches break down, formed through real production experience rather than theory. • Genuine curiosity about the brand intelligence problem — what it means to encode creative judgment, how you represent things that were never written down, how you know when a model's understanding is actually right. You don't need a marketing background, but you should find these questions interesting. • You take ownership of outcomes, communicate clearly when something isn't working, and follow the problem rather than your specialisation.
Responsibilities
• Build the knowledge layer that sits underneath Superads' AI agents — the systems that give them genuine understanding of a brand rather than just access to its documents. • Design how brand knowledge is represented, stored, and continuously updated: the structures that let an agent reason about a brand the way a senior strategist would, not just retrieve what's been written down. • Develop agentic search capabilities — systems that let agents reason about what they don't know, identify knowledge gaps, and navigate information dynamically rather than relying on fixed retrieval pipelines. • Evaluate and iterate on architectures for knowledge retrieval and reasoning, identifying where current approaches break down and driving more interesting solutions. • Translate emerging AI research and patterns into production-ready systems that measurably improve output quality and reliability. • Work closely with the product and AI engineering teams to ensure the knowledge layer directly improves what users experience — staying connected to product impact even when the work takes you deep into infrastructure.
Benefits
• Superside's vision is to create equal opportunities globally by accelerating the world’s transition to online work. With that in mind, we're building a fully remote company that attracts people where they are. • Remote-first. Customer-led. • Remote isn’t just a perk; it’s how we deliver better for customers. We are fully committing to our customers by hiring top talent and collaborating seamlessly across time zones. • Global team, local impact. • High performance, low ego. • Work in a fast-paced, high-trust environment where feedback is direct, growth is constant, and kindness leads collaboration. • Impact meets opportunity. • We’re in the sweet spot — big enough to be stable, small enough for you to shape what’s next. Your ideas will matter here. • Grow fast. Lead well. • You’ll gain mentorship, take on real responsibility, and grow your career while helping us disrupt a global industry.
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