About Savvy Wealth:

Wealth management is a $545 billion industry in the US, yet remains archaic and inefficient with low technology penetration. 75% of financial advisors don’t offer digital communication beyond email, and 62% still build financial plans manually in Excel. This leads to a poor client experience and results in financial advisors spending over 70% of their time on non-client facing, manual work.

Savvy is changing that. We’re building the most advisor-centric platform in wealth management: a digital-first solution that modernizes human financial advice. Advisors who partner with Savvy tap into AI-powered software, automated sales and marketing, and seamless back office workflows to scale faster and spend more time with clients.

We’ve raised over $105M to date from Thrive Capital, Index Ventures, Canvas Ventures, Mark Casady (former LPL Financial CEO), and other top-tier investors. Our team is made up of repeat founders and operators who’ve helped build Airbnb, Square, Brex, Carta, Facebook, $200B+ RIAs, and more.

Savvy is at a pivotal point in its growth trajectory, having established strong product-market fit in providing a modern platform to financial advisors. We’ve surpassed $5.1 billion in AUM in less than three years, grown 600%+ in the last 18 months, and are entering the next phase of the company which involves rapid expansion of our product offering and continued revenue growth. Come help us scale!

The role:

Savvy is hiring a Senior Engineer to lead the design and delivery of complex product and platform work. Our platform is where AI meets fiduciary advice, and the senior engineers who build it don't just use AI to go faster, they make decisions about where AI belongs in the system, how to build it reliably, and how to raise the team's ability to do the same. You'll own end-to-end delivery of high-impact projects, establish engineering patterns for the team, and help define how our platform evolves as we scale.

Responsibilities:

Lead the design and delivery of complex product features and platform systems, from scoping and architecture through production and iteration.
Establish engineering patterns and standards for the team: how we build, test, observe, and iterate across both product and platform work.
Apply and champion AI tooling (Claude Code, Cursor, Codex, and the rest) to accelerate your own output and raise the team's velocity.
Drive architectural decisions: data models, service boundaries, system tradeoffs, and communicate them clearly to technical and non-technical stakeholders.
Mentor engineers, give substantive feedback, and be a go-to resource for technical judgment across the team.
Partner with Product and Design to shape scope and de-risk execution on high-ambiguity problems.
Work directly with our customers (financial advisors) to understand their workflows and bring that context into how you build.

Must have:

5+ years of professional experience.
You use AI tools aggressively in your daily workflow: Claude Code, Cursor, Codex, and whatever else is useful. You're consistently ahead of the curve on what's emerging, and you translate that into concrete decisions: what to build with AI, how to build it reliably, and where it's not worth the complexity.
Track record of leading projects end-to-end with measurable business impact; you've taken ambiguous problems from 0 to production and held the quality bar throughout.
Strong full-stack or platform engineering depth; we use Rails, React, Next.js, PostgreSQL, and GraphQL; comfortable across the stack or with the depth to close gaps fast.
Strong system design instincts: data models, service boundaries, failure modes, and how systems hold up at scale.
Strong technical communication: you write clearly, give effective feedback, and collaborate well across functions in a startup environment.

Nice to have:

You've built AI-powered features or systems that customers rely on in production: LLM integrations, agentic workflows, retrieval pipelines, intelligent automations, or similar. You understand the real design tradeoffs: prompt reliability, latency, cost, failure modes, not just the happy path.
Experience with LLM evaluation frameworks (RAGAS, LangSmith, custom harnesses) and a systematic approach to measuring reliability.
Fintech domain knowledge: financial services, wealth management, regulatory compliance, or financial data integrations.
Experience with vector databases, embedding pipelines, or retrieval-augmented generation at production scale.
Modern development ecosystem fluency: macOS toolchains, CI/CD pipelines, IaaS (AWS/GCP), and observability platforms (Datadog, Honeycomb, etc.).

Benefits:

Competitive salary and equity package
Unlimited PTO + paid company holidays
Access to holistic medical, dental, and vision plans
Company 401(k), Commuter, and HSA/FSA plans
NYC office in the heart of Manhattan
Lunch and snacks provided in the office
Access to virtual mental health care (Spring Health), vision related benefits (XP Health), and health concierge (Rightway) to help you find the right care
Access to counseling for stress management, dependent care, nutrition, fitness, legal, and financial issues (Guardian WorkLifeMatters EAP)

Senior Engineer - Technical Staff