Senior Engineering Manager
Compass
| Company | Compass |
| Category | Engineering |
| Location | New York City |
| Remote | On-site (inferred) |
| Employment | Not stated |
| Level | Manager |
| Salary | Not stated by the employer |
| Posted | 12 Jun 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (greenhouse) |
Description
At Compass, our mission is to help everyone find their place in the world. Founded in 2012, we’re revolutionizing the real estate industry with our end-to-end platform that empowers residential real estate agents to deliver exceptional service to seller and buyer clients. As the Senior Engineering Manager for the AI Platform Team , you will lead the AI Engineering Hub of our newly established Staff AI Enablement Organization. In this highly visible role, you will bridge the gap between complex infrastructure and real-world business impact. Your mandate is two-fold: overseeing the Tier 1 Platform Foundation (building reusable, secure AI primitives like agent inference, prompt tuning, and orchestration) and coordinating the Tier 2 Staff Enablement efforts (partnering directly with departments like Finance, Legal, and Transaction Management to deploy deep, domain-specific workflow automations).
You will manage a lean, high-caliber, hybrid team of full-time Compass software engineers—ranging from Junior to Staff-level —alongside a flexible pool of strategic contractors. By treating the platform as a product, you will build a secure, unified "AI Platform Flywheel" that protects proprietary company data while systematically cutting operational overhead to capture millions in business efficiency.
Responsibilities:
Lead and Develop Talent: Directly manage, mentor, and grow a hybrid team of full-time engineers and contractors. Cultivate a high-performing culture through individualized coaching, clear performance standards, and proactive career pathing.
Drive AI Platform Strategy: Formulate and execute the roadmap for foundational AI platform primitives (agent orchestration, LLM gateway, telemetry, secure caching, etc.) in close collaboration with senior leadership and Principal Engineers.
Accelerate Business Enablement: Deeply partner with corporate departments (Finance, Legal, Ops, etc.) to identify automation opportunities, translating operational processes into structured AI integrations that run on your platform primitives.
Enforce Strict AI Governance: Oversee technical design and architecture to ensure all AI tools strictly adhere to information security, data residency, and identity and access management (IAM) guidelines.
Promote Operational Excellence: Establish and monitor clear performance metrics (accuracy, latency, token consumption, and cost observability). Implement robust logging, alerting, and rapid incident response systems.
Balance Strategic Resources: Make critical, data-driven decisions on team structure and resource allocation, deciding when to leverage flexible contractors for short-term velocity versus retaining core technical architecture inside our FTE footprint.
Deliver Compelling Communication: Drive high-level technical and strategic written communication (e.g., system tenets, architectural plans, and project charters) to align multiple cross-functional stakeholders around technical trade-offs.
Requirements:
Strong Technical Background: 10+ years of software engineering experience, with a proven track record of building scalable developer platforms, APIs, SaaS infrastructure, or centralized backend frameworks.
Direct People Management: 6+ years of experience leading software engineering squads, with proven success managing senior and staff-level engineers, as well as geographically distributed teams.
Fluency in the Generative AI Stack: Deep familiarity with modern LLM application architectures, vector databases, prompt design, fine-tuning, retrieval-augmented generation (RAG), and agent orchestration libraries.
Hybrid Team Stewardship: Experience managing a blended team model of full-time employees and contractors, keeping quality bars high while driving execution velocity.
Comfort with Ambiguity: A proven self-starter who can take open-ended business problems and shape them into clear, structured, and phased engineering pl
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