Staff Software Engineer, CKD

NerdWallet is hiring a hands-on Staff Software Engineer to lead the technical direction and build integrations that bring its financial guidance to third-party AI assistants. The role focuses on designing reliable, reusable, secure LLM-backed systems and partnering across engineering, product, security, legal, and compliance.

Responsibilities:

• Lead the technical direction for AI platform integrations. Own the architecture for how NerdWallet's guidance is packaged, exposed, and rendered inside third-party AI assistants, from tool and protocol design to in-conversation UI
• Build a lot of it yourself. Write production code for new integrations, prototype new platform capabilities as they launch, and unblock teams on the hardest technical problems
• Design for reuse across platforms. Define the abstractions, contracts, and patterns that let multiple platform teams share a common foundation while still using each platform's unique features
• Adapt as platforms change. Track evolving platform protocols, SDKs, review processes, and policies. Turn those changes into roadmap and architecture decisions before they become blockers
• Make quality measurable. Help define eval and testing strategy for platform integrations, including automated evals, regression suites, and end-to-end tests across environments you don't fully control
• Build safely for a regulated domain. Partner with Security, Legal, and Compliance so integrations handle authentication, consent, and sensitive consumer data correctly and follow financial compliance requirements
• Own reliability and performance. Set standards for monitoring, latency, cost, and incident response on platform-facing services, and help resolve production issues when they happen
• Raise the engineering bar. Lead design reviews, set coding and architecture standards, and conduct code reviews that model what good looks like
• Mentor and multiply. Coach engineers across FTE and contractor teams on system design, LLM-backed development, and good engineering practices
• Partner with leadership on the roadmap. Work with Engineering Managers and Product to shape priorities, estimate effort and risk honestly, and recommend where to place technical bets
• Use data to guide decisions. Dig into usage and performance data to find where integrations are working, where they aren't, and what to build next

Requirements:

• 8+ years in software engineering, with at least 3+ years at the Staff level and deep hands-on experience building and operating production backend systems
• A track record of technical leadership: architecting complex systems end to end, leading a team through hard technical problems, establishing best practices, and mentoring other engineers
• Hands-on experience building production features on LLMs: tool use/function calling, MCP or similar protocols, prompt and context design, retrieval (RAG), evals, and handling non-deterministic output
• Advanced knowledge of a modern TypeScript stack (e.g., Node.js, React, GraphQL, Postgres, Redis), with the judgment to evaluate unfamiliar codebases, SDKs, and vendor tools
• Experience designing APIs and shared services that other teams build on, including versioning, backward compatibility, and balancing competing consumer needs
• Experience building on third-party platforms or ecosystems (e.g., app stores, plugin/extension ecosystems, partner APIs) where you work within someone else's constraints and review processes
• Strong understanding of authentication and authorization patterns (e.g., OAuth) and security best practices for handling sensitive data
• Comfort with early-stage, zero-to-one work where the product, platform, and process are being defined as you go
• Strong communication skills: you can explain AI system behavior, tradeoffs, and risk clearly to engineers, product partners, and leadership
• Experience building apps, connectors, or agents for major AI assistant platforms
• Experience shipping AI features in regulated industries (fintech, lending, insurance, healthcare), including privacy, consent, and compliance review
• Experience with AWS, modern CI/CD, containerization, and observability for LLM systems (tracing, cost and latency monitoring)
• Experience mentoring engineers across blended FTE and vendor/contractor teams
• Comfort in a fast-paced environment where priorities shift as platforms and user behavior evolve