Silver
Prospera AI - AI Backend Engineer
4mo ago
60000 –90000 USD / yearSeniorRemotellmapiparallelizationvector databasesprompt managementversioninga/b testing
Responsible for designing and optimizing AI/Backend systems for a scalable multi-agent AI orchestration platform in wealth management.
Responsibilities
- 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.
Requirements
- 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
Conditions
- 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)
How to apply
- 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
Other
- 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.
- 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
- 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