Senior Engineering Manager

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 plans with minimal guidance.
• Customer Empathy & Product Mindset: Demonstrated ability to understand the pain points of internal "customers" (non-technical business departments) and package platform capabilities into intuitive, reliable internal products.
• Security & Compliance Aptitude: Solid understanding of enterprise security concepts, including IAM, data isolation, encryption, and regulatory compliance standards (e.g., SOC 2, PCI DSS) as they relate to cloud-based applications.