AI​/Backend Engineer

We're building Sophie, a multi-agent AI orchestrator that helps wealth management advisors deliver more personalized, effective service to their clients. Our platform analyzes behavioral patterns, communication preferences, and emotional states to transform how advisors understand and serve their clients. We're a small, well-funded team at an exciting inflection point — our technology works, customers love the product, and now we're building the engineering team to scale.

We're looking for an AI/Backend Engineer to own and evolve our LLM orchestration pipeline. You'll be the first dedicated engineering hire, working directly with our CTO to transform Sophie from a working prototype into a scalable, enterprise-ready platform. This is a high-impact, high-autonomy role. You'll shape technical decisions that define the product for years to come.

• • Design and optimize our multi-agent orchestration system
• • Implement parallelization and streaming to dramatically reduce response latency
• • Build robust prompt management with versioning and A/B testing capabilities

• • Design retrieval-augmented generation for accurate, contextual responses
• • Work with vector databases, embeddings, and relevance scoring
• • Optimize for both speed and accuracy at scale

• • Build developer-friendly APIs connecting our AI capabilities to the frontend
• • Design for future integrations with CRMs and advisor tools
• • Implement proper authentication, rate limiting, and documentation

• • Establish code review practices and testing standards
• • Contribute to technical patents and IP development

• • 4+ years production Python experience (async patterns, type hints)
• • Hands-on experience with LLM APIs (OpenAI, Anthropic, or similar)
• • Strong understanding of prompt engineering and multi-step LLM workflows
• • Strong SQL and Postgre
  
  SQL skills

• • Experience with RAG systems and vector databases (Pinecone, Weaviate, pgvector)
• • Fin Tech or regulated industry background

• • Self-directed and comfortable with ambiguity
• • Strong written communication (async-first culture)
• • Pragmatic problem-solver who ships iteratively
• • Collaborative mindset with ego-free approach to feedback

• • Not a pure ML/research role — you'll apply LLMs, not train them
• • Not a management role — near-term focus is individual contribution
• • Not fully autonomous — you'll collaborate closely with the CTO on architecture
• • Not 9-to-5 — startup intensity applies, though we respect work-life balance

Base Competitive — Based on experience and location

Equity Meaningful early-stage grant with 4-year vesting

Equipment Professional laptop provided + remote work stipend after 6 months

Time Off Flexible PTO with minimum 15 days encouraged

Schedule Flexible hours with 3–4 hours daily overlap Americas timezones

Total timeline: 2–3 weeks

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