Scale Engineer

Engineering Manager, Compose

Engineering Manager · Manager · Full Time · Remote

United States Remote · RemoteUSD 180k – 280k6d ago
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Role

What you'll do.

Lead Mural's AI-native Compose team as an Engineering Manager, scaling an ambitious product from early access to production-grade reliability. You'll combine hands-on technical leadership with team management, driving architecture decisions and shipping LLM-powered features while building a high-performing remote engineering culture focused on experimentation and sustainable velocity.

Responsibilities

  • Team Leadership and Development: Lead, hire, and grow a full-stack engineering team through structured 1:1s, performance management, and coaching. Establish clear expectations and career development paths while maintaining high psychological safety and fostering a culture of continuous learning in an AI-first product development environment.
  • Technical Direction and Architecture: Own technical strategy for the Compose product, setting engineering standards across code quality, testing, and observability. Lead architecture discussions with credibility, review critical pull requests, and establish best practices for LLM integration, AI agent development, and production-grade AI feature reliability.
  • Product Delivery and Experimentation: Drive end-to-end delivery of AI-native features using rapid experimental loops: ship to real users, measure impact, iterate quickly, and maintain reliability at scale. Partner with Product and Design as co-owner of the roadmap, translating customer feedback and usage data into prioritized engineering work.
  • Engineering Excellence: Raise engineering craft across testing strategies, observability and monitoring systems, and AI-assisted development tools. Implement quality frameworks for LLM evaluation, cost optimization, and model context integration while modeling Mural's remote-first, transparent work culture at a sustainable pace.
  • Stakeholder Communication: Communicate technical tradeoffs, risks, and progress clearly to product, business, and customer stakeholders. Translate complex AI implementation challenges into business-friendly context and lead cross-functional discussions on feature prioritization, scalability, and cost-benefit analysis.

Qualifications

What we look for.

Technical

  • Full-Stack Architecture

    Solid technical foundation with ability to lead architecture discussions across frontend, backend, and AI/ML systems. Experience building scalable applications with modern web frameworks and cloud infrastructure.

  • AI Agent and LLM Systems (Preferred)

    Familiarity with building AI agents, retrieval-augmented generation (RAG) systems, knowledge graphs, or Model Context Protocol (MCP). Understanding of prompt engineering, LLM evaluation frameworks, and cost optimization strategies.

  • Production Observability

    Expertise in monitoring, observability, and reliability practices for complex distributed systems. Experience with logging, metrics, tracing, and debugging production issues at scale.

  • Code Quality and Testing

    Strong understanding of testing strategies including unit testing, integration testing, and end-to-end testing frameworks. Ability to establish quality standards and automate testing in CI/CD pipelines.

Education

  • Computer Science or Related Field

    Bachelor's degree in Computer Science, Software Engineering, or equivalent professional experience building production software systems (degree preferred but not required).

Experience

  • Management Experience

    2+ years of direct people management of software engineers with demonstrated responsibility for hiring, coaching, performance management, and team development at scale.

  • Software Engineering Foundation

    5+ years of professional software engineering experience building and operating production applications. Must have hands-on technical work within the last 3-4 years to maintain credibility in code reviews and architecture discussions.

  • AI/LLM Production Experience (Preferred)

    Proven experience leading engineering teams that shipped LLM-powered features to production, including AI model evaluation, quality monitoring strategies, cost management, and handling production AI systems.

  • Distributed Team Leadership

    Experience building and scaling high-performing engineering teams in remote-first or fully distributed environments with asynchronous communication practices.

Skills

Required

  • People Management

    Ability to hire, develop, and retain engineering talent. Strong coaching skills, performance management, and talent development with empathy-driven leadership.

  • Technical Leadership

    Credible hands-on technical ability with recent production engineering work. Comfortable leading architecture decisions, reviewing code, and setting technical standards.

  • Full-Stack Engineering

    Solid understanding of frontend, backend, and infrastructure challenges. Experience with building and shipping complete product features across multiple layers.

  • Experimentation and Data-Driven Decision Making

    Bias toward rapid experimentation, learning from metrics and user feedback, and changing direction based on evidence. Comfort with uncertainty and iterative development.

  • Communication and Collaboration

    Excellent written and verbal communication skills. Ability to explain technical concepts to non-technical stakeholders and facilitate cross-functional collaboration.

  • Remote-First Leadership

    Experience building trust and psychological safety in distributed environments. Strong asynchronous communication practices and ability to maintain team cohesion across time zones.

Preferred

  • LLM and AI Systems

    Nice to have

    Direct experience shipping production LLM-powered features, understanding model evaluation, RAG systems, prompt engineering, and cost management for AI workloads.

  • AI Agent Architecture

    Nice to have

    Familiarity with AI agent frameworks, retrieval systems, knowledge graphs, or Model Context Protocol (MCP). Understanding of agentic workflows and multi-step AI reasoning.

  • Product and Design Partnership

    Nice to have

    Experience working as an engineering leader co-owning product roadmaps, translating customer insights into technical strategy, and collaborating closely with product and design teams.

  • High-Growth Scaling

    Nice to have

    Experience scaling products and teams rapidly from early-stage to production reliability. Understanding of how to maintain quality and velocity as user base grows exponentially.

Tech stack

Languages

JavaScript/TypeScriptPython

Frameworks

ReactNode.jsLLM Frameworks

Databases

MongoDBVector Databases

Tools

Azure OpenAIGit and Version ControlCI/CD SystemsObservability and Monitoring

Other

Model Context Protocol (MCP)LLM Evaluation FrameworksPrompt Engineering and Fine-tuningRetrieval-Augmented Generation (RAG)

Compensation

Pay and benefits.

Base·USD 180,000 – 280,000

Equity·Stock options

Benefits

  • Remote-First Work Environment

    Fully distributed team model supporting work from anywhere. Flexible working hours and asynchronous-first communication to enable global collaboration across time zones.

  • Health and Wellness Coverage

    Comprehensive health insurance, dental, and vision coverage. Mental health support and employee wellness programs aligned with remote-first working practices.

  • Equity Compensation

    Stock options with standard vesting schedules. Opportunity to benefit from company growth as Mural scales its AI-powered collaboration platform.

  • Professional Development

    Learning and development budget for courses, conferences, and technical certifications. Support for staying current with AI/ML trends and leadership development programs.

  • Flexible Time Off

    Generous paid time off policy with flexible vacation days. Support for sabbaticals and personal development time.

  • Home Office Setup

    Equipment stipend for remote workspace setup including monitor, desk, chair, and ergonomic accessories to support long-term remote productivity.

  • Parental Leave

    Extended parental leave policy supporting work-life balance for new parents across all genders.

  • Inclusive Culture

    Commitment to diversity and inclusion with reasonable accommodation for individuals with disabilities throughout the employment experience.

Process

Interview steps.

  1. 01

    Application and Screening

    Review of your resume, cover letter, and background to assess alignment with technical experience, management history, and AI/LLM familiarity. Mural may contact you to discuss your experience with production AI systems and team leadership.

  2. 02

    Initial Conversation with Hiring Manager

    30-45 minute conversation with the engineering leadership team to discuss your management philosophy, technical background, and experience shipping AI-powered products. Expect questions about your approach to code review standards, team development, and rapid iteration cycles.

  3. 03

    Technical Architecture Discussion

    Deep dive into technical capabilities and architectural thinking. You'll discuss system design challenges, technology tradeoffs for AI integration, and approach to building reliable LLM systems. Bring examples of architectures you've led.

  4. 04

    Leadership and Culture Fit Conversation

    Discussion with Mural's product, design, or executive leadership about leadership philosophy, remote-first practices, and alignment with Mural's experimental, transparent culture. Expect scenarios on handling team challenges and prioritizing sustainability.

  5. 05

    Team Interviews

    Conversations with members of the Compose team to discuss collaboration style, technical depth, and how you'd work with engineers. This is your opportunity to learn about team dynamics and technical challenges.

  6. 06

    Final Decision and Offer

    Feedback synthesis and offer extension if aligned. Mural typically discusses compensation, equity, and start timeline. Expect discussion of your onboarding plan and first 30/60/90 day priorities for the team.

Full posting

Original listing.

ABOUT THE TEAM

The Mural Compose team is ambitious and fast-moving. We are passionate builders who love to experiment and iterate. Our project is seeking to leverage the latest technology in AI to acquire new customers and expand our revenue base as broadly as possible. This team is at the front of our product strategy and future growth.

 

YOUR MISSION

You'll lead the team behind one of Mural's most important bets. In the near term, you'll take our AI native product from early access to a product that customers rely on every day, raising quality, reliability, and speed as more users come on board.

Expect a very hands-on role. You'll review PRs, set the technical standards the team builds to, and stay close to the code and architecture decisions. You'll also keep the team's pace high and sustainable while building a high-performing team in a remote-first way.

 

WHAT YOU'LL DO

  •  Lead, hire, and grow a team of full-stack engineers through regular 1:1s, clear expectations, coaching, and performance management.

  • Own delivery end to end with a fast, experimental loop: ship early to real users, measure what works, and iterate quickly without losing reliability.

  • Partner with Product and Design as co-owners of the Compose roadmap, using customer feedback and usage data to decide what to build, cut, or double down on.

  • Raise engineering craft across testing, observability, and AI-assisted development, and model Mural's remote-first, work-in-public culture at a sustainable pace.

WHAT YOU'LL BRING

  •  2+ years managing software engineers directly, with responsibility for hiring, coaching, and performance management.

  • 5+ years of prior experience as a software engineer building and operating production applications, with hands-on technical work in the last 3–4 years.

  • A solid technical foundation, enough to lead architecture discussions and review code with credibility.

  • A bias for experimentation: you make sound calls quickly, learn from data, and change course when the evidence says so.

  • A people-first approach: you lead with empathy, listen first, and build the trust and psychological safety that help each person do their best work.

  • Excellent communication skills, including explaining technical tradeoffs clearly to product, business, and customer stakeholders.

  • Experience leading a team that shipped LLM-powered features to production, including evaluation, quality monitoring, and cost management.

  • Experience building AI agents, retrieval systems, knowledge graphs, or familiarity with Model Context Protocol (MCP).

Our Stack

Azure OpenAI, React, Node, MongoDB

Equal Opportunity 

We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

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