Staff Software Engineer – Web

A Place for Mom

20h•$170,000 - $210,000

About The Position

A Place for Mom is seeking a hands-on technical leader to direct the architecture and technical direction of its public web experiences. The role focuses on full-stack web engineering, with deep front-end and rendering expertise and working knowledge of Next.js, data stores, and content systems. The engineer will select technologies, architecture patterns, and design approaches, and provide technical leadership and mentorship to the engineers who build and maintain the web platform. The position owns the quality and evolution of a high-traffic platform used by families searching for senior care. It requires understanding how pages are rendered, cached, crawled, and measured, including the trade-offs among SEO, performance, and cost. The role also treats experimentation, analytics, and AI as core parts of engineering. The Staff Software Engineer reports to the Senior Manager of Engineering – Web and partners with product, design, marketing, SEO, and peer engineering teams. Responsibilities include leading a Next.js and React platform, improving mobile performance and technical SEO, building Node.js services and APIs, evolving the headless CMS, developing experimentation and analytics foundations, strengthening quality and deployment practices, resolving production issues, and architecting smaller AI features and shared AI frameworks.

Requirements

10+ years of software engineering experience with JavaScript/TypeScript, React, and Node.js, including experience with high-traffic public websites.
Deep expertise in Next.js or a similar framework and rendering strategies, including SSR, SSG/ISR, CSR, hydration, and streaming, and their impact on SEO, performance, and cost.
A proven track record improving Core Web Vitals and mobile performance using tools such as Lighthouse, CrUX, and real-user monitoring.
Strong technical SEO knowledge, including understanding how JavaScript rendering affects search engines.
Working back-end knowledge of Node.js APIs and services, MongoDB, and relational databases.
Understanding of headless CMS concepts, including content modeling, preview, and publishing workflows.
Understanding of experimentation, feature flagging, and product analytics, including test design, flag lifecycle, event tracking, and data quality.
Hands-on experience building LLM-backed features, including prompt design, retrieval, structured output, evaluation, and cost and latency management.
Fluency with AI coding agents.
Experience with AWS, CDNs, and edge caching.
Strong communication skills and ability to explain a technical vision simply to audiences at every level.
A track record of technical leadership, setting standards, mentoring engineers, and owning quality from design through production.

Nice To Haves

Experience with GraphQL.
Hands-on experience with the listed stack: TypeScript, React, Next.js, Node.js, GraphQL, MongoDB, Sanity, PostHog, Segment, AWS, GitHub Actions, and AI coding agents such as Claude, Codex, or Gemini.
Programmatic SEO at scale, such as thousands of templated location or listing pages.
Experience with SEM landing pages and conversion rate optimization.
Experience with edge rendering and middleware, such as Vercel, CloudFront, or similar.
Experience in healthcare, senior care, or privacy-aware analytics and consent management.

Responsibilities

Lead the architecture of the Next.js and React web platform, selecting appropriate rendering strategies for each page type.
Own mobile-first performance and Core Web Vitals, set budgets, monitor real users, and drive measurable improvements.
Partner with SEO and marketing on technical SEO, including crawlability, indexation, structured data, canonicals, redirects, sitemaps, and SEM landing pages.
Build Node.js services and APIs using MongoDB and relational data stores, with caching at edge and server layers.
Evolve the Sanity headless CMS so content and marketing teams can publish pages without engineering bottlenecks.
Build experimentation and analytics foundations, including feature flags, A/B tests, SSR-safe flag evaluation, and a trustworthy event taxonomy.
Promote quality and continuous deployment through unit, integration, and end-to-end testing, pipeline automation, and design system adoption.
Review code, create reference implementations, and mentor engineers across the team.
Resolve production issues across the browser, CDN, rendering, and service layers, and prevent recurrence.
Partner with product and project managers to deliver work on time and keep technical documentation current.
Architect smaller AI features end to end, including retrieval, orchestration, failure modes, and monitoring.
Guide teams in responsible AI patterns, testing, and observability.
Partner with Product to assess the feasibility, technical risk, cost, and scalability of AI features.
Identify repeatable AI frameworks and components that can become paved paths for other teams.
Improve AI evaluation practices, including quality scoring, metrics, and fallbacks.
Use AI coding agents in daily work and help define how the team adopts them.