Senior Engineer - Technical Staff

Wealth management is a $545 billion industry that still runs on manual work. 75% of advisors offer no digital communication beyond email, and most still build financial plans by hand in Excel. Savvy is reinventing what it looks like to be a financial advisor. Founder Ritik Malhotra saw the fragmentation firsthand after seeking out his own advisor, and started Savvy to give independent advisors a modern, AI-native home.

Savvy is a registered investment advisor (RIA), and we partner with experienced financial advisors who want to grow without running the back office themselves. Advisors bring their book and join Savvy, running under their own brand (or ours), and Savvy earns a percentage of the assets they manage. In return, they get a true business-in-a-box: a proprietary tech platform and client portal, an in-house marketing team that helps them grow, a world-class investment management team, and a dedicated client services team that runs day-to-day operations and support. Advisors at Savvy service up to 50% more households and save 19 hours a week.

AI runs through everything we do. On the product side, Savvy Intelligence (released April 2026) is the only AI built for wealth managers that can see a client's complete financial picture. Internally, everyone at Savvy uses Claude and is encouraged to experiment with it, backed by a dedicated AI enablement team and a RevOps org building agents in-house.

The trajectory is steep and it's still early. We're a Series C company with 170+ people, $200M raised, and $100M ARR in sight this year. Inc. ranked us the No. 1 fastest-growing financial services company in America in 2026. Come build the next stage with us!

We're a Certified Great Place to Work and have been honored for our culture and our growth:

• Newsweek's America's Greatest Startup Workplaces (2026)

• Fortune Best Workplaces in New York™ (2026)

• Great Place to Work Certified™
  
  

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.

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  Lead the design and delivery of complex product features and platform systems, from scoping and architecture through production and iteration.

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  Establish engineering patterns and standards for the team: how we build, test, observe, and iterate across both product and platform work.

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  Apply and champion AI tooling (Claude Code, Cursor, Codex, and the rest) to accelerate your own output and raise the team's velocity.

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  Drive architectural decisions: data models, service boundaries, system tradeoffs, and communicate them clearly to technical and non-technical stakeholders.

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  Mentor engineers, give substantive feedback, and be a go-to resource for technical judgment across the team.

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  Partner with Product and Design to shape scope and de-risk execution on high-ambiguity problems.

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  Work directly with our customers (financial advisors) to understand their workflows and bring that context into how you build.

• 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.

• 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.).