About Nivalto + AURA
Nivalto (currently in stealth mode) is building AURA, a next-generation AI orchestration platform for high-net-worth (HNW) and ultra-high-net-worth (UHNW) families, their advisors, and trusted collaborators. AURA combines intelligent asset vaults, gifting and trust workflows, AI-generated summaries, financial nudges, and advisor collaboration tools into a seamless, privacy-first experience.
At its core is a multi-agent AI system that coordinates wealth, legacy, estate, and lifestyle workflows — with deep consent layers, Circle-based roles, and auditable interactions across generations.
Your Role
As Co-Founder & CTO, you’ll be the technical architect of AURA — leading the vision, stack, infrastructure, and engineering culture from 0→1. You’ll define our system architecture, AI orchestration layer, Vault infrastructure, and data pipelines — while recruiting our early technical team and preparing for institutional diligence and scale.
This is a foundational leadership role for a builder with deep experience in secure systems, AI-powered infrastructure, and complex multi-party collaboration platforms.
Key Responsibilities
AI Platform & System Architecture
- Architect and own the AURA backend: a multi-agent AI framework that handles task routing, memory, summarization, nudges, and multi-user orchestration
- Design scalable, modular infrastructure (multi-tenant and single-tenant variants) across tiers: CORE, PRIME, BLACK
- Implement secure data tagging, trust/estate mappings, and privacy-based visibility permissions
- Oversee integrations with language models (e.g., GPT, Claude), vector databases, and agent routing infrastructure
Security, Compliance & Vault Infrastructure
- Design and implement AURA Vault: a digital asset storage system with document tagging, gift/ownership logic, and encryption
- Ensure audit logging, role-based access, and redacted data views are core to the platform
- Architect for GDPR, SOC2, and HIPAA-lite compliance from day one
- Lead conversations with family offices and CTO-level advisors on data custody, isolation, and risk architecture
Engineering Leadership & Delivery
- Recruit, hire, and lead an elite team of engineers across AI, backend, and infrastructure
- Define the initial sprint cadence, QA/release pipeline, and technical onboarding playbooks
- Collaborate with the CEO and product team on feature prioritization, roadmap scope, and investor-readiness
- Lead Seed round technical diligence, partner assessments, and enterprise-grade architecture reviews
Integrations & Ecosystem Buildout
- Architect secure integrations with external systems like Addepar, Salesforce, Plaid, iLevel, Carta, and CPA document systems
- Build APIs to support third-party advisors, trusted Circle members, and potential marketplace partners
- Prepare AURA for future SDK or developer access layers, with modular agent plug-ins
What We’re Looking For
- 10+ years in engineering, AI systems (has completed a multi-agent production grade implementation), or secure platform architecture
- Proven experience building intelligent platforms from the ground up (zero-to-one)
- Deep understanding of cloud architecture (e.g., CoreWeave, AWS, GCP), vector databases, LLM APIs, and agentic task design
- Passion for privacy-first systems that must earn trust from HNW/UHNW users, advisors, and institutions
- A strong architectural thinker who can balance velocity, modularity, and long-term scalability
- Builder mindset with high agency and clear, collaborative communication
Preferred Experience Includes:
- Leading AI and infrastructure startups (e.g., OpenAI, Anthropic, Cohere, Adept, Inflection AI)
- Scalable WealthTech or financial data platforms (e.g., Addepar, Envestnet, Black Diamond, Arch)
- Elite engineering orgs at Apple, Google, Meta, Amazon, Microsoft, or Palantir
- Security-forward or privacy-first platforms in legal tech, fintech, or enterprise (e.g., Ironclad, Stripe, Plaid, Twilio, Brex)
- AI orchestration or multi-agent architecture teams (research or production)
Education
- Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Software Engineering, AI/ML, or related technical fields
- Preference for advanced degrees (MS, PhD) in AI, Data Engineering, or Systems Architecture from top-tier institutions