Staff Software Engineer - Full Stack

A Place for Mom

2d•$160,000 - $200,000•Remote

About The Position

A Place for Mom is building the next generation of intelligent, scalable platforms that connect families, providers, and advisors through AI-driven experiences. We are looking for a talented Staff Software Engineer – Full Stack to help build and scale the platform our B2B partners run their business on. Our team owns the agency portal where senior living and home care providers manage referrals and their relationship with A Place for Mom. This position reports to the Senior Engineering Manager – B2B Platform. You will work across the full stack: React/TypeScript experiences in Grace, .NET services behind our unified API layer, and Python ingestion pipelines that pull provider data from NPPES, state licensing boards, and other sources into Databricks. You will help select the technologies, architectural patterns, and design approaches the team adopts, and provide technical direction to a team of engineers building the systems our partners depend on every day. We expect this engineer to work with LLMs as a first-class part of the job. That means using agentic coding tools fluently to move faster, and building LLMs into the product where it creates real leverage - data extraction and normalization at scale, entity resolution, classification, and workflow automation. Candidates who treat LLMs as an afterthought will not be a fit for this role.

Requirements

10+ years of software engineering experience, with demonstrated depth on both sides of the stack
Strong proficiency with modern front-end development — React, TypeScript, component architecture, state management, testing, and design system adoption
Strong proficiency building and operating back-end services and APIs in any modern server-side language, plus solid relational data modeling and SQL
Working proficiency in Python for data ingestion, transformation, and automation
Demonstrated proficiency with AI-assisted and agentic development workflows — for example Claude Code or similar coding agents, MCP-based tool integrations, and AI-assisted code review — with concrete examples of how it changed your team’s throughput or quality
Practical experience building LLM-backed features: prompt design, retrieval and context strategy, structured output, cost and latency management, and evaluating output quality systematically
Experience with cloud infrastructure (AWS preferred) and modern data platforms such as Databricks, Snowflake, or equivalent
Thrives in fast-paced environments while architecting dependable solutions that scale effectively
Role models and champions modern ways of working — Agile, DevOps, and related practices — and actively participates in an engineering community
Strong communication and storytelling skills: able to articulate a vision or concept in simple terms to a broad audience at every level
Helps position our services and products to take advantage of changing industry trends and opportunities
Is able to step back from a task and reassess size and complexity when appropriate
Takes ownership of the quality of the solution or feature being implemented
Demonstrates competent problem-solving skills — debugging, analysis, and instrumentation — in a context beyond code they have written
Takes ownership of keeping technical documentation for their features up to date

Nice To Haves

Experience with B2B or partner-facing SaaS platforms, marketplaces, or lead and referral management systems
Experience with large-scale web scraping, crawling, or third-party data acquisition, including the operational realities of upstream sources that change without notice
Experience with entity resolution, record linkage, or master data management
Healthcare, senior care, or regulated-data domain experience (NPPES, state licensure, HIPAA awareness)
Experience building internal developer tooling or MCP servers that make AI agents effective against proprietary systems

Responsibilities

Design, build, and continuously deploy features across the stack — React/TypeScript front ends, .NET service and API layers, and the data pipelines behind them
Build partner-facing experiences in Grace that make referral management, community profiles, and reporting genuinely easier for agency users
Use AI coding agents as a core part of your daily workflow — scoping work for agents, reviewing and hardening their output, and building the context, prompts, and tooling that make agentic development reliable on our codebase
Apply LLMs to product and data problems where they outperform hand-written rules — extraction from unstructured provider records, classification, matching, and summarization — with evaluation harnesses and guardrails so quality is measured rather than assumed
Collaborate with leads to design cloud-native, service-oriented components and APIs
Enable continuous deployment by championing quality engineering practices: linting, unit testing, integration and e2e testing, and pipeline automation
Peer review code, suggest optimizations, and create reference implementations that raise the bar for the team
Help define engineering best practices including how the team adopts and governs AI tooling and provide technical mentorship
Investigate and resolve production issues end to end, from the UI through the service and data layers, and work to prevent recurrence
Partner with product and project managers so deliverables land on time and at high quality, and keep technical documentation for your areas current