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Engineering Manager, Compose

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Remote from
UK, USA, Spain
Salary
USD 176,645–252,350 / yr
Employment
Full Time
Experience
Senior
Published
Apply before
19 Nov 2026
Listing views
30
Application actions
2
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AI Summary

The role, at a glance.

Mural is seeking a hands-on Engineering Manager to lead the Compose team as it evolves an AI-native product from early access into a reliable, widely used offering. The role combines direct people management with technical leadership, including code reviews, architecture decisions, engineering standards, and end-to-end delivery. The manager will partner closely with Product and Design to run rapid experiments informed by customer feedback and usage data. Success requires prior management experience, strong full-stack production engineering experience, and demonstrated delivery of LLM-powered capabilities. The team works remote-first and expects clear communication, sustainable execution, and a strong culture of trust and accountability.

Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

Job Complexity

5/5
EasyHard

Pace & Pressure

5/5
RelaxedFast-paced

Autonomy Level

5/5
GuidedFull ownership

Communication Load

5/5
IndependentCollaborative
AI insightThis is a senior leadership role with accountability for both team performance and the technical quality, reliability, cost, and delivery speed of an AI product. It requires balancing hands-on engineering judgment with hiring, coaching, roadmap partnership, and rapid experimentation.

Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job median (per year)Market rate
$214,497.50
US market range (per year)$180k–$280k
AI insightThe employer-disclosed annual base-pay range is $176,645–$252,350 USD, with a midpoint of $214,497.50. This is a credible range for a senior Engineering Manager leading AI product delivery in the US market; estimated comparable annual market compensation is approximately $180,000–$280,000 USD.

Core skills

Skills and capabilities most closely associated with this opportunity.

Sample interview questions
How have you balanced hands-on technical leadership with managing and developing engineers?

I set clear ownership boundaries and maintain a regular operating cadence of 1:1s, feedback, and career conversations, while staying involved in high-leverage technical decisions. I review critical designs and pull requests, but delegate implementation ownership so engineers can grow and the team does not depend on me as a bottleneck.

Describe an LLM-powered feature you brought to production and how you measured its quality.

I would define product-specific quality metrics before launch, combining offline evaluation sets with production signals such as task success, user feedback, latency, error rates, and cost per successful outcome. I would use staged rollout, monitoring, and structured failure analysis to improve prompts, retrieval, guardrails, or model selection.

How would you run a fast experimental loop without compromising reliability?

I would break initiatives into small, measurable releases with explicit hypotheses and success criteria. Feature flags, telemetry, automated testing, rollback plans, and service-level expectations allow the team to learn quickly while protecting customers and maintaining operational discipline.

How do you partner with Product and Design when deciding what to build or stop building?

I treat Product and Design as co-owners of outcomes rather than downstream stakeholders. We align on customer problems, evidence, constraints, and measurable goals, then use qualitative feedback and usage data to prioritize, revise, or stop work quickly when the evidence changes.

What practices help create a high-performing remote engineering team?

I establish transparent goals, written decision records, predictable communication norms, and regular one-on-ones. I also create space for asynchronous collaboration, recognize contributions publicly, address conflict directly, and ensure every engineer has clarity on expectations, support, and growth opportunities.

This analysis is generated from the job description. Salary estimates, role characteristics and sample answers are guidance, not employer-provided facts.
Opportunity details

About this role.

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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