Senior Staff Engineer

Superloop is a small, focused team inside Superside building AI-powered systems that understand a brand’s identity and history, then deliver that context wherever creative work happens. Today we’re shipping tools for context-powered briefing and scoping; next up are persistent brand memory, instant quoting, and first-draft generation, all built with a practical, production mindset.

We’re hiring a very senior hands-on engineer to be the leading individual contributor for Superloop. This is not a people-management role. You’ll write production code, own key architectural decisions, and mentor engineers while collaborating closely with Product and Design. If you thrive in fast-moving environments, enjoy solving complex technical challenges, and want to shape how brands scale creative work with AI, this is your chance.

What you'll do

• Own the architecture for capturing, storing, and serving brand context at scale.

• Build the platform: services, data models, indexing/search, APIs, and integrations.

• Deliver LLM features the right way: RAG, embedding pipelines, evaluation harnesses, guardrails, and observability.

• Prototype quickly, productionize what works, and kill what doesn’t.

• Partner with Product and Design to scope features and validate solutions with users.

• Lead by example: code reviews, technical RFCs, pairing, and mentoring.

• Document decisions clearly (ADRs, design docs) to keep alignment across the team.

• Contribute to integrations with Superside systems and customer tools.

What you’ll bring

• 8+ years building and scaling backend production systems in TypeScript/Node and/or Python (JVM/Spring Boot is a plus).

• Proven 0 to 1 track record, taking systems from prototype to scaled product.

• Expertise in schema design, indexing, caching, vector stores, and query optimization.

• Practical LLM/GenAI delivery experience (RAG, orchestration, evaluation, safety).Strong API design skills (REST/GraphQL, event-driven patterns, messaging).Clear product sense and the ability to explain technical trade-offs to non-technical partners.

• Ownership mindset: bias for action, comfort with ambiguity, and focus on outcomes.

• Experience with knowledge management, search, CMS/DAM, or enterprise integrations.

• Familiarity with MCPs, agent frameworks, LangChain/LlamaIndex, or similar tooling.