About the Role

Elayne is an Applied AI company reimagining how families organize, protect, and transfer their estates, from financial accounts and legal documents to digital assets and end-of-life wishes. We combine structured data, custom AI agents, and guided UX to make estate optimization and post-loss settlement fast, clear, and dignified.

We integrate with banks, insurance providers, legal systems, and data aggregators to create a real-time, intelligent view of an individual or family’s estate. Then we proactively adapt to life events (like having a child or losing a parent), and automate complex legal-financial workflows that typically take families years to finish.

We’re an Accel and YC-backed seed stage company, launched last year and we’re operating in a manual $260B TAM, with over $80T in assets expected to transfer in the coming decades. This is a greenfield market for AI, and we intend to define the category.

Your Mission:

As the Founding Senior Engineer (AI/ML), you’ll build production-grade AI systems that are technically rigorous, reliable, and scalable.

Working closely with the founding team, you’ll design and implement LLM-based features using RAG, vector search, and multi-step agent workflows to address challenges like entity resolution, document classification, and contextual memory management.

You’ll play a key role in developing core infrastructure for prompt orchestration, embedding pipelines, and real-time inference, while optimizing for latency, cost, trust, and personalized outcomes.

Your work will shape how millions of families navigate one of life’s most difficult transitions: losing a loved one. In this senior role, you’ll have the autonomy to move quickly, prototype novel architectures, and translate complex ML systems into intuitive, deeply human experiences.

What We’re Looking For:

• Builder’s mindset: you move fast, take full ownership, write reliable systems, and are obsessed with solving real problems
• 4+ years of engineering experience shipping production-grade AI features or infrastructure
• Strong Python and AI/ML background, with experience building agentic or RAG-based systems using LangChain, vector DBs, and evaluation frameworks
• Skilled in building scalable full-stack solutions using TypeScript, NestJS, PostgreSQL, AWS and modern data tools
• Thrive in ambiguity, urgency, and rapid iteration - ideally you’ve been part of a high intensity seed stage startup before (we work long hours, but have a lot of fun together)
• Based in NYC and excited to work in-person at our NoMad HQ

What You’ll Do:

• Design and build AI-native product features like document parsing, task checklists, and smart suggestions
• Integrate models (OpenAI, Anthropic, OSS) into workflows using LangChain, custom pipelines, or purpose-built flows
• Collaborate with the founding team on technical scoping, architecture, and infrastructure decisions
• Contribute to embedding strategies, feedback loops, and prompt tuning frameworks
• Define and implement evaluation frameworks to measure output quality, user trust, latency, and model performance
• Stay on the frontier of AI tooling and infrastructure and bring practical innovations into production

Current stack: React, TypeScript, NestJS, PostgreSQL, Redis, AWS, OpenAI, Auth0. You don’t need to know everything, but we value engineers who learn fast and aren’t afraid to jump in

Upcoming challenges include building memory across sessions, reliable summarization pipelines, and intelligent fallback mechanisms for partially structured data.

We’ll be a great fit if you’re looking for:

• A rare chance to build an iconic company with actual human impact; not just another AI CRM or dev tool
• An opportunity to grow into a technical leader, mentor others, and set the technical and ethical foundations for how AI guides financial and legal decisions
• YC, Accel, and mission-aligned investors backing a product with massive, untapped demand

Compensation:

Salary range $160k–$250k, depending on experience and qualifications

Meaningful equity package is included; final composition will be determined by level, scope, relevant experience, and cash vs equity preference. Benefits/PTO included.

Additional detail