About Us

Wealth.com is the industry’s leading estate planning platform, empowering more than 1,000 wealth management firms to modernize how they talk about estate planning with their clients. As the only tech-led, end-to-end platform built specifically for financial institutions, Wealth.com enables firms to drive scale, efficiency, and measurable client impact. Trusted by some of the largest names in finance, Wealth.com combines proprietary AI, robust security, and deep technological and legal expertise to serve the full range of client needs, from foundational plans to the most sophisticated estate strategies. The company has been widely recognized for innovation and leadership, winning Top Estate Planning Technology and Top Estate Planning Implementation at the 2025 WealthManagement.com Industry Awards, being named the 2024 Best Technology Provider in the Trust category, and earning #1 in estate planning market share in the 2025 Kitces AdvisorTech Study.

Our team is fundamental to our standing as the leading estate planning platform. We cultivate a collaborative and supportive environment, fostering innovation and making Wealth.com a truly enjoyable workplace. Wealth.com is proud to be certified as a Great Place to Work for 2025.

The Role

We are seeking a Software Engineer, AI/ML (Infrastructure & Platform) to build the foundational systems that power our next generation of AI applications.

This is a systems-focused role. You will design and build the platforms, abstractions, and infrastructure that enable teams to reliably develop, deploy, and scale AI systems — including agentic workflows, retrieval pipelines, and model integrations.

You will operate at the intersection of AI systems and distributed infrastructure, focusing on the “how” behind production AI: how models are orchestrated, how tools/skills are exposed and executed, and how systems are evaluated, monitored, and scaled in real-world environments.

Your work will directly enable product teams to move faster while ensuring our AI systems are reliable, observable, secure, and cost-efficient.

What You Will Do

Build core AI infrastructure

Design and implement platforms for LLM orchestration, tool execution, and agent workflows
Develop shared services and abstractions used across multiple AI applications

Build AI capability layers (tools / skills)

Design and implement tools (“skills”) that agents and applications rely on, including APIs, workflows, and integrations
Define clear interfaces for capabilities such as data retrieval, calculations, document processing, and external system actions
Build reusable, composable abstractions that enable safe and scalable tool usage across systems
Ensure tools are reliable, observable, and secure, especially when interacting with sensitive data

Enable agentic systems at scale

Build infrastructure to support multi-step agents (state management, tool routing, retries, failure handling)
Design systems where agents reason over and invoke tools/skills reliably
Create reusable orchestration patterns between models and capabilities

Develop evaluation and observability systems

Build frameworks for offline and online evaluation of AI systems
Implement logging, tracing, and monitoring for model behavior and system performance

Own reliability and performance

Design systems for high availability, fault tolerance, and graceful degradation
Optimize for latency, throughput, and cost across AI workloads

Build data and retrieval infrastructure

Develop scalable RAG pipelines, indexing systems, and data processing workflows
Own infrastructure for handling large-scale structured and unstructured data

Create internal platforms and developer tooling

Build tools, SDKs, and internal platforms that enable engineers to integrate AI capabilities quickly and safely
Standardize best practices across teams (prompting, evaluation, deployment)

Work closely with product and AI teams

Partner with AI Applications engineers to support production use cases
Translate product needs into scalable infrastructure solutions

Qualifications

A degree in Computer Science, Engineering, or a related quantitative field (or equivalent practical experience)
Strong software engineering fundamentals, including system design, distributed systems, and writing maintainable code
Proven track record of building and operating production systems at scale
Proficiency in Python, TypeScript, C#, and comfort working across a polyglot stack, picking up new languages and frameworks as needed
Experience building backend systems, APIs, or infrastructure platforms
Experience working with AI/ML systems in production, including LLM integrations or data pipelines
Experience designing or integrating systems with tool/skill abstractions (e.g., function calling, APIs, or capability layers used by AI systems)
Ability to operate in ambiguous, fast-moving environments with high ownership

Preferred Qualifications (Bonus Points)

Experience building AI platforms or infrastructure layers (not just applications)
Experience with:
- RAG systems, vector databases (e.g., Pinecone, Weaviate, pgvector)
- Agent orchestration frameworks (e.g., LangGraph, LangChain, or custom systems)
- Evaluation and observability tooling for AI systems
Experience designing or building tooling layers (skills/capabilities) for AI systems
Experience designing scalable distributed systems or platform abstractions
Experience with cloud infrastructure such as:
- GCP (Cloud Run) or AWS (ECS, Lambda)
- Containerized or serverless deployments
Experience with event-driven systems, queues, and async processing
Experience with MLOps, CI/CD, and production monitoring
Experience working in regulated domains (LegalTech, FinTech, HealthTech)
Familiarity with data privacy and security techniques (e.g., PII handling, redaction)

You Might Be a Fit If

You enjoy building systems and platforms that other engineers depend on
You think in terms of abstractions, capabilities, and reusable systems
You care about how AI systems behave in production at scale
You’re comfortable working across AI systems and infrastructure layers
You take ownership of ambiguous problems and drive them to robust solutions

You Might Not Be a Fit If

You prefer working primarily on frontend or user-facing features
Your experience is limited to experimentation without production systems
You are less interested in infrastructure, reliability, or platform design

Benefits & Perks

Competitive salary.
Hybrid work in the New York area
Excellent medical, dental, and vision insurance options, with low-cost premium structures that demonstrate our commitment to offering great value to our employees.
100% company-paid basic life insurance, short-term and long-term disability insurance.
100% paid parental leave upon eligibility.
Company equity managed through Carta.
401k with match and 100% vesting upon hire.
Flexible PTO in an environment where taking time off to relax or recharge is supported and encouraged.
Take time off for holidays—and yes, your birthday counts too. Celebrate, relax, and recharge without thinking twice.

Wealth is an equal opportunity employer and encourages people from all backgrounds to apply. Should you have a disability or special need that requires accommodation, please let us know.