Job description

About Monstro Monstro provides the AI-powered Financial Intelligence System for regulated financial institutions. It enables banks and wealth managers to deliver continuous, personalized, governed Financial Guidance to every client, not just the top tier, across their entire financial life: saving, borrowing, investing, planning, protecting, and preparing. Meaningful Financial Guidance has only ever been available to a small portion of people. We are changing that, through the institutions people already trust. Institutions already have the relationships, the data, and the context to understand each client; Monstro turns that understanding into guidance that helps each person understand, decide, and act. For clients, that means clearer decisions, proactive support when life changes, and a better view of their financial lives. For institutions, it means deeper relationships, more clients served consistently, and more of each client’s financial life managed in one place. What makes this possible is how the system is built. Governance is not an added feature; it is foundational. Every recommendation reflects the institution’s own views, policies, and permissions. Every output can be audited, traced, and reversed, and client data stays under the institution’s control. Generative AI is used to build and configure the system; at runtime, execution is deterministic, so every output can be explained and stood behind, not just trusted. The work We are building for a high-stakes industry where the work has real consequences. Guidance only matters if people can trust it and institutions can govern it. The challenge is to make Financial Guidance more personal and more available without making it less trusted: to build AI that institutions can audit, explain, and reverse, in a domain where being wrong carries real cost. That is what makes the problem hard, and the work meaningful. This is not a simple AI problem; it takes product judgment, technical depth, regulatory discipline, design quality, and a team that moves quickly without lowering the bar. Monstro is moving from vision to market: launching with financial institutions, growing the team, and building for the enterprise in one of the most regulated industries. You will be expected to think clearly, communicate directly, move with urgency, hold a high standard, and take responsibility for work that matters. We are an early team building something ambitious, and what you do here will shape both the product and the company. About the Role We're looking for a Staff Software Engineer to support our AI application development team at the heart of the company's mission. This is a deeply technical role with real scope: you'll architect and ship systems that power AI-driven financial analysis, build the tooling and infrastructure that domain experts rely on, and set the engineering bar for how we build AI systems responsibly in a regulated industry. You'll influence how we design agents, how we validate and govern AI output, how we scale our modeling infrastructure, and how we think about auditability and compliance. This isn't a role where AI is a thin wrapper — the intelligence layer is the product. What You'll Do Architect and build AI agent systems — including multi-agent workflows, orchestration layers, and the infrastructure that makes them reliable and auditable in production Work at the edge of what’s possible with modern AI — rapidly evaluating new models, tools, and development patterns, and setting the technical direction for turning the most promising capabilities into robust production systems. Design modeling and reasoning systems that meet the correctness and explainability requirements of financial services — where every recommendation needs to be traceable and defensible Build internal applications and platforms (Python/React) that enable domain experts and engineers to author, validate, and deploy AI-powered analysis at scale Document your decisions, ensure sufficient test coverage and generate AI native artifacts to share your work with others Own distributed backend infrastructure: event-driven workers, job pipelines, and multi-stage processing systems that deliver AI outputs reliably under load Establish patterns for AI output validation and quality assurance — including automated evaluation pipelines, hallucination detection, and compliance guardrails Drive technical decisions across teams: schema design, API contracts, system boundaries, and service architecture Contribute to full stack application development Lead engineering initiatives across team members and cross functional partners Establish and promote engineering and architecture best practices and the adoption of new AI technologies and techniques Mentor senior engineers and raise the engineering bar across the organization What We're Looking For 8+ years of engineering experience, with a track record of leading complex systems from design to production. Deep curiosity about where AI-native software is heading, with the technical judgment to separate promising new capabilities from hype and help shape how emerging approaches are adopted across the engineering organization. Hands-on experience designing, building, and shipping production software systems using AI development tools, especially AI-powered software Strong software engineering skills and experience with a demonstrated track record contributing to best practices application architecture Python expertise — async services, type-safe code, and systems that scale Strong distributed systems fundamentals: event-driven architectures, message queues, job state machines, and worker patterns Relational database fluency and an instinct for data modeling Full-stack range — you can build product-quality React/TypeScript UIs when the problem calls for it Opinionated about how AI systems should be tested, evaluated, and monitored in production Experience leading technical teams or acting as a force multiplier across engineering Preferred but not required Hands-on experience with AI/ML systems — agent architectures, LLM integration, model evaluation, or AI pipelines in production Opinionated about how AI systems should be tested, evaluated, and monitored in production Experience designing multi-agent systems, agentic workflows, or AI orchestration layers Data engineering experience developing data pipelines handling big data Experience contributing to cloud infrastructure using infrastructure as code Background in quantitative finance, financial planning, or wealth management technology Experience building AI systems in regulated industries (financial services, healthcare, legal) or with compliance, auditability, or explainability requirements Why Monstro? Impact : Build technology that helps millions of people make better financial decisions, through the institutions they already trust, and help define the category of Financial Intelligence. Ownership : High trust, high ownership, high standards. You will own meaningful problems end to end from day one. Experienced team : Work with leadership that has a track record of scaling companies from early stage to major exits. Principles-driven culture : We move fast, because the opportunity is urgent. We communicate directly, because clarity saves time. We hold a high standard, because institutions and clients need to trust what we build. In person, in New York : We are headquartered at The Spiral in Hudson Yards and work in the office four days a week, because our pace depends on fast collaboration. Compensation and benefits : Competitive cash compensation and meaningful equity, plus 100% employer-paid medical, dental, and vision coverage, disability coverage, flexible PTO, paid parental leave, and catered meals. Base Compensation Range (New York City): $224,000 - $264,000 Final compensation will depend on a variety of factors, including experience, skills, internal leveling, and market conditions, and will be offered within the stated range in accordance with applicable pay transparency laws. A Note on Interviewing: We sometimes use AI note-takers to help us transcribe interview notes, so we can be more present in your interview. If you’d like to opt out of us using automatic transcribers, please note this in the free text field in your application; otherwise we’ll take your application as confirmation that you’re happy for us to use note-takers (whether added to video calls or in the background). Ready to Build With Us? The standard is simple: do great work, own the outcome, communicate with purpose, move with urgency, raise the level. If that sounds like you, we’d love to hear from you.

Requirements

Must-haves

Architect and build AI agent systems — including multi-agent workflows, orchestration layers, and the infrastructure that makes them reliable and auditable in production
Design modeling and reasoning systems that meet the correctness and explainability requirements of financial services — where every recommendation needs to be traceable and defensible
Build internal applications and platforms (Python/React) that enable domain experts and engineers to author, validate, and deploy AI-powered analysis at scale
Document your decisions, ensure sufficient test coverage and generate AI native artifacts to share your work with others
Own distributed backend infrastructure: event-driven workers, job pipelines, and multi-stage processing systems that deliver AI outputs reliably under load
Establish patterns for AI output validation and quality assurance — including automated evaluation pipelines, hallucination detection, and compliance guardrails
Drive technical decisions across teams: schema design, API contracts, system boundaries, and service architecture
Contribute to full stack application development
Lead engineering initiatives across team members and cross functional partners
Establish and promote engineering and architecture best practices and the adoption of new AI technologies and techniques
Mentor senior engineers and raise the engineering bar across the organization
8+ years of engineering experience, with a track record of leading complex systems from design to production.
Hands-on experience designing, building, and shipping production software systems using AI development tools, especially AI-powered software
Strong software engineering skills and experience with a demonstrated track record contributing to best practices application architecture
Python expertise — async services, type-safe code, and systems that scale
Strong distributed systems fundamentals: event-driven architectures, message queues, job state machines, and worker patterns
Relational database fluency and an instinct for data modeling
Full-stack range — you can build product-quality React/TypeScript UIs when the problem calls for it
Opinionated about how AI systems should be tested, evaluated, and monitored in production
Experience leading technical teams or acting as a force multiplier across engineering
Hands-on experience with AI/ML systems — agent architectures, LLM integration, model evaluation, or AI pipelines in production
Opinionated about how AI systems should be tested, evaluated, and monitored in production
Experience designing multi-agent systems, agentic workflows, or AI orchestration layers

Nice-to-haves

Preferred but not required

Application prep

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Keywords to mirror

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Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

Dental

Vision

Pto

Parental Leave