About Monstro

Monstro is a governed AI platform for regulated financial institutions. We give banks and wealth managers a way to deliver trusted advice digitally — to every client, not just the top tier.

Institutions already have the relationships, data, and context to understand each client. Monstro turns that understanding into advice. It gives every client the experience of a personal advisor: bringing together their full financial picture, identifying what matters, and delivering personalized guidance across investments, tax, retirement, insurance, legal, and more.

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. Every recommendation reflects the institution's own views, policies, and permissions. Every output is auditable, traceable, and reversible, and client data stays under the institution's control. Generative AI shapes how advice is designed; 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. The challenge is to make advice 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 a hard problem, and it is the reason to be here.

You will work on technology that brings real financial advice to people who have rarely had access to it. You will be expected to think clearly, move with urgency, hold a high bar, 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 Senior Applied AI Software Engineer to support our AI 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

• 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 tooling platforms (Python/FastAPI) that enable domain experts and engineers to author, validate, and deploy AI-powered analysis at scale

• 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

What We're Looking For

• 5-8+ years of engineering experience, with a track record of leading complex systems from design to production

• Hands-on experience with AI/ML systems — agent architectures, LLM integration, model evaluation, or AI pipelines in production

• Python expertise — async services, type-safe code, and systems that scale

• Experience building AI systems in regulated industries (financial services, healthcare, legal) or with compliance, auditability, or explainability requirements

• 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

Nice to Have

• Experience designing multi-agent systems, agentic workflows, or AI orchestration layers

• Background in quantitative finance, financial planning, or wealth management technology

• Experience leading technical teams or acting as a force multiplier across engineering

Why Monstro?

Ownership & Impact: Shape the future of AI-powered finance—building a category-defining product used by consumers and institutions around the world.

Experienced Team: Join a team with leadership that has a track record of scaling companies from early stage to major exits.

Principles-Driven Culture: Work in a culture that values speed, ownership, and impact—what most companies achieve in 90 days, we do in 45.

Comprehensive Compensation Package: Competitive salary, equity, and robust benefits package, including paid health, vision, dental, and disability coverage.

Base Compensation Range (New York City): $194,000 - $235,000

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?

If you're excited to contribute to a high-bar team building something meaningful, we'd love to hear from you.