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
Document architecture decisions for future team members
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
Production API development experience (FastAPI or similar)
Strong SQL and PostgreSQL skills
Experience with RAG systems and vector databases (Pinecone, Weaviate, pgvector)
Streaming/real-time implementation experience (SSE, WebSockets)
TypeScript/JavaScript familiarity
FinTech or regulated industry background
Strong UX intuition—you notice when flows have one too many clicks
Pragmatic perfectionism—you know when to polish and when to ship
Clear communicator who can explain technical constraints in business terms
Collaborative mindset—frontend doesn’t exist in isolation
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
We want to be upfront about expectations:
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
Equity: Meaningful early-stage grant with 4-year vesting
Equipment: Professional Laptop ready to work with AI provided + stipend for remote work when 6 month mark is met
Time Off: Flexible PTO with a minimum 15 days encouraged
Learning: $1,000 annual professional development budget
Schedule: Flexible hours with 3-4 hours daily overlap (Americas timezones)
Silver.dev Recruiter Screen
Silver.dev System Design Screen
Technical Screen & System Design Interview with Tech Lead + CTO
Assessment Deep-Dive with Senior Engineer + CTO
Culture Fit Check with CEO
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