About Prospera AI 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.
About Prospera AI 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.
The Role 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.
What You'll Do Own the AI Pipeline 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
Build RAG Systems Design retrieval-augmented generation for accurate, contextual responses
Work with vector databases, embeddings, and relevance scoring
Optimize for both speed and accuracy at scale
Develop Production APIs 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
Shape the Foundation Establish code review practices and testing standards
Document architecture decisions for future team members
Contribute to technical patents and IP development
What We're Looking For Must Have 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
Great to Have 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
How You Work 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
What This Role Is Not 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
Compensation & Benefits BaseCompetitive — Based on experience and location
Meaningful early-stage grant with 4-year vesting
Professional laptop provided + remote work stipend after 6 months
Flexible PTO with minimum 15 days encouraged
Annual professional development budget
Adaptable hours with 3–4 hours daily overlap Americas timezones
Interview Process Resume Review— 1–2 day turnaround
Technical Screen— 60 min video conversation with CTO
Take-Home Assessment— 4–6 hours (to be reviewed)
Assessment Deep Dive— 90 min collaborative review
Values & Fit— 45 min conversation
References & Offer
Total timeline: 2–3 weeks

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📌 AI/Backend Engineer (Torreón)
🏢 Prospera AI
📍 Torreón