Maxwell

Design and maintain features across Rails and TypeScript services, integrate external mortgage platforms, lead technical design, mentor engineers, and join on-call rotations. | Requires 7+ years building production web applications, deep Ruby on Rails and React expertise, distributed-systems and security knowledge, and use of AI-assisted coding tools. | Senior Fullstack Engineer Your Opportunity: We're building a category-defining company at the intersection of real estate, technology, business services, and the consumer. As a profitable, hypergrowth startup on the path to an IPO, our standards are high, our team is scrappy, and our commitment is to execute the best work of our lives. This is YOUR CHANCE to shape the backbone of a company that's scaling rapidly and innovating boldly. As our Senior Fullstack Engineer, you'll partner with the CTO, founders, and executives to build and scale our mortgage technology platform, shipping features end to end across a mix of microservices and monolith architectures, with a focus on backend systems and third-party integrations. If you thrive in complexity, entrepreneurial problem-solving, and believe in scaling through tech and AI, this is your PLACE. Who Develops You: CTO What You're Great At: You are a seasoned engineer with 7+ years building and running production web applications, and you take a problem from a vague description to a shipped, monitored solution. You go deep on Ruby on Rails, including API-only services, ActiveRecord, PostgreSQL, background jobs, and RSpec. You're also comfortable shipping polished UI with React and TypeScript, and you've worked with GraphQL (ideally Apollo) on both server and client. You've built distributed, event-driven systems and know how to debug failures that span services, using retries, idempotency, and eventual consistency. You've also tamed third-party integrations (REST, SOAP, webhooks) and partner APIs that are slow, inconsistent, or poorly documented. You treat sensitive personal and financial data with care and have strong instincts for security and multi-tenant data isolation. You use AI and agentic coding tools at an advanced level every day, can describe how you structure context for agents and verify what they produce, and you build tooling that makes other engineers more effective. You communicate clearly: you can write a strong design doc, explain a production incident to a customer success manager, and disagree productively with a product manager. You own production through on-call, incident response, observability, and blameless postmortems. Bonus points if you have experience in mortgage tech or a similar regulated, integration-heavy domain (fintech, lending, insurance, payments, healthcare), familiarity with LOS platforms (Encompass, MortgageBot, Byte) or MISMO standards, Node.js/TypeScript services, Elasticsearch, Redis, Docker, AWS, CI/CD, saga or workflow orchestration patterns, or a history of mentoring engineers and leading cross-team projects. What You'll Do: Design, build, and maintain features across Rails API services, TypeScript/Node services, a GraphQL gateway, and React frontends Own integrations with external platforms (LOS systems, mortgage insurance providers, document and e-sign vendors), including data mapping, sync and reconciliation, retries, and idempotency Design and evolve asynchronous, multi-step workflows using message queues (RabbitMQ, SNS/SQS), Sidekiq background jobs, and saga-style orchestration Keep our multi-tenant platform correct and secure, respecting partner boundaries in every query and event Lead technical design for significant features by writing design docs and architecture decision records, weighing trade-offs, and building alignment before you build Identify and pay down technical debt, improving service boundaries, module design, test coverage, and developer experience Hold a high bar in code review and help set engineering standards across the team Join the on-call rotation, lead incident response, and follow through on root-cause fixes that prevent recurrence Use observability tools and CI/CD to keep the platform healthy, and improve them where they fall short Work directly with Customer Support & Success on lender-reported escalations, reproducing issues, investigating sync problems with external LOSs, and explaining findings clearly to non-engineers Partner with Product Managers to refine requirements, uncover edge cases early, and propose simpler alternatives Work with UI/UX Designers to turn designs into polished, accessible interfaces, and push back constructively when technical constraints affect the experience Mentor other engineers through pairing, code review, and design feedback, including on effective AI-assisted workflows Lead on AI-assisted engineering by using agentic coding tools (Claude Code, Cursor, Codex) daily to plan, implement, test, debug, and review, and by delegating well-scoped work to agents and reviewing their output rigorously Build and maintain shared AI tooling for the team, including agent instruction files (CLAUDE.md/AGENTS.md), reusable skills and prompts, MCP servers connecting agents to internal systems, and automated workflows Set and follow guardrails for AI use: verify agent output, never expose secrets or customer data, and know when a task needs a human-written solution Why Maxwell: We believe people do their best work when they're trusted, supported, and surrounded by others who are equally driven. That's why this role includes a "work from the place you work best" approach – at home, in an office, or on the move. Our competitive benefits include PTO as needed, comprehensive insurance coverage, a 401(k) match, stock option grants, and a stock purchase plan. Every team member is an owner, building the place they are proud to call "my company."

Design and deliver production-grade AI and agentic systems, own architecture, observability, and cost management, and collaborate with product and engineering teams. | 6+ years software engineering with 2+ years shipping production LLM or ML systems, strong Python and cloud infrastructure skills, and experience with agentic workflows and retrieval systems. | Who We Are Maxwell is a mortgage technology and fulfillment company on a mission to make lending simpler, faster, and more accessible. Our platform powers hundreds of lending institutions across the country, from independent mortgage banks and credit unions to community banks. Our mortgage Point of Sale is our flagship product, supported by loan origination, document intelligence, and private-label fulfillment capabilities. We are a remote-first team that takes craft seriously and moves with intention. We are building a cutting-edge AI company in mortgage technology. Our document intelligence capabilities are live in production today. This role exists to accelerate what we have and ship the next generation of AI and agentic systems. Who You Are You are an applied AI engineer who ships. You have taken LLM-based systems and agentic workflows from prototype to production, and you know what that requires: evals, observability, cost management, latency tuning, error handling, and iteration. You have opinions about agent frameworks and architectures, built from what you have shipped. You are also pragmatic enough to pick the right tool for the job rather than force a favorite into every problem. You read new research, try new approaches, and form your own view on what holds up in production. You work across the stack. You can design a retrieval system, wire up tool calls, build an eval harness, debug a production outage, and explain your choices to a product manager or an executive in the same day. What You Will Own Your scope from day one includes: Design and delivery of production AI and agentic systems across document intelligence, workflow automation, and copilots Architecture decisions for LLM-based systems, including retrieval, tool use, orchestration, memory, and evaluation Evals and observability for production AI. You own how we know the system is working and how we catch it when it is not Cost and latency management at production volume Partnership with AI product on scoping and sequencing features Partnership with data engineering on the pipelines, schemas, and data quality your systems depend on Technical mentorship of other engineers working on AI-adjacent systems Vendor and model evaluation, including POCs, benchmarks, and cost-performance tradeoffs Must Haves 6+ years of software engineering experience, with at least 2 years focused on shipping production LLM-based or ML systems. Demonstrated experience building and deploying agentic systems, including tool use, orchestration, and multi-step workflows. Strong Python proficiency, including production-grade code quality, testing, and deployment practices. Hands-on experience with LLM APIs (Anthropic, OpenAI, AWS Bedrock, or similar), including prompt design, structured outputs, and function calling Production experience with evals and observability for LLM systems. You know how to measure accuracy, detect regressions, and monitor drift. Experience with retrieval systems (RAG), vector databases, and embedding models. Fluency with cloud infrastructure (AWS preferred), including serverless, containers, and API design. Clear written and verbal communication skills with the ability to write design docs,.explain tradeoffs, and collaborate with product and engineering peers. Ownership mindset - Ships work end-to-end rather than handing off. Nice to Haves Fintech, mortgage, or regulated industry experience Experience with document AI, OCR pipelines, or structured extraction workflows Familiarity with AWS Bedrock, SageMaker, or equivalent cloud AI services Experience with modern agent frameworks (LangGraph, CrewAI, AutoGen, custom) and a clear point of view on when each is appropriate Experience with modern data warehouses (Snowflake, BigQuery) and transformation tools (dbt) Contributions to open source AI or ML projects Experience operating production systems on-call What Success Looks Like Within 60 days, you have shipped a meaningful improvement to an existing AI capability or a new one into production Within 90 days, evals and observability are in place for the systems you own AI systems run reliably at production volume with predictable cost and latency Other engineers on the team ship AI work faster and with higher quality because of the patterns and tooling you have established You are the person product and engineering leadership trust to give a straight answer on what is shippable, what is not, and what it will take Salary Band: $90,000 – $150,000 (depending on experience and location)