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 EquityMeaningful early-stage grant with 4-year vesting EquipmentProfessional laptop provided + remote work stipend after 6 months Time OffFlexible PTO with minimum 15 days encouraged LearningAnnual professional development budget ScheduleFlexible hours with 3–4 hours daily overlap Americas timezones Interview Process 1 Resume Review— 1–2 day turnaround 2 Technical Screen— 60 min video conversation with CTO 3 Take-Home Assessment— 4–6 hours (to be reviewed) 4 Assessment Deep Dive— 90 min collaborative review 5 Values & Fit— 45 min conversation 6 References & Offer Total timeline: 2–3 weeks

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