Senior Software Engineer, AI/ML (AI Infrastructure & Platform)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 RoleWe 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 DoBuild Core AI InfrastructureDesign and implement platforms for LLM orchestration, tool execution, and agent workflowsDevelop shared services and abstractions used across multiple AI applicationsBuild AI Capability Layers (Tools / Skills)Design and implement tools ("skills") that agents and applications rely on, including APIs, workflows, and integrationsDefine clear interfaces for capabilities such as data retrieval, calculations, document processing, and external system actionsBuild reusable, composable abstractions that enable safe and scalable tool usage across systemsEnsure tools are reliable, observable, and secure, especially when interacting with sensitive dataEnable Agentic Systems at ScaleBuild infrastructure to support multi-step agents (state management, tool routing, retries, failure handling)Design systems where agents reason over and invoke tools/skills reliablyCreate reusable orchestration patterns between models and capabilitiesDevelop Evaluation and Observability SystemsBuild frameworks for offline and online evaluation of AI systemsImplement logging, tracing, and monitoring for model behavior and system performanceOwn Reliability and PerformanceDesign systems for high availability, fault tolerance, and graceful degradationOptimize for latency, throughput, and cost across AI workloadsBuild Data and Retrieval InfrastructureDevelop scalable RAG pipelines, indexing systems, and data processing workflowsOwn infrastructure for handling large-scale structured and unstructured dataCreate Internal Platforms and Developer ToolingBuild tools, SDKs, and internal platforms that enable engineers to integrate AI capabilities quickly and safelyStandardize best practices across teams (prompting, evaluation, deployment)Work Closely with Product and AI TeamsPartner with AI Applications engineers to support production use casesTranslate product needs into scalable infrastructure solutionsQualificationsA 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 codeProven track record of building and operating production systems at scaleProficiency in Python, TypeScript, C#, and comfort working across a polyglot stack, picking up new languages and frameworks as neededExperience building backend systems, APIs, or infrastructure platformsExperience working with AI/ML systems in production, including LLM integrations or data pipelinesExperience 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 ownershipPreferred 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 systemsExperience designing or building tooling layers (skills/capabilities) for AI systemsExperience designing scalable distributed systems or platform abstractionsExperience with cloud infrastructure such as:GCP (Cloud Run) or AWS (ECS, Lambda)Containerized or serverless deploymentsExperience with event-driven systems, queues, and async processingExperience with MLOps, CI/CD, and production monitoringExperience working in regulated domains (LegalTech, FinTech, HealthTech)Familiarity with data privacy and security techniques (e.g., PII handling, redaction)You Might Be a Fit IfYou enjoy building systems and platforms that other engineers depend onYou think in terms of abstractions, capabilities, and reusable systemsYou care about how AI systems behave in production at scaleYou're comfortable working across AI systems and infrastructure layersYou take ownership of ambiguous problems and drive them to robust solutionsYou Might Not Be a Fit IfYou prefer working primarily on frontend or user-facing featuresYour experience is limited to experimentation without production systemsYou are less interested in infrastructure, reliability, or platform designBenefits & PerksCompetitive salary.Hybrid work in the New York areaExcellent 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.