Full-Stack Engineering Manager

Details

• You thrive at the intersection of hands-on technical leadership and people management — you're equally comfortable in a design review and a 1:1 conversation about career growth
• You believe great managers unblock their teams by being technically credible, not by staying out of the code
• You've built and shipped production AI systems and know what it takes to take an agentic workflow from prototype to enterprise reliability
• You're energized by ambiguity — you can take a fuzzy business need from a VP of Sales and turn it into a concrete engineering roadmap
• You care about building an inclusive, high-trust team where engineers grow and do the best work of their careers
• Lead, hire, and develop a team of 4–7 senior engineers across the full GTM AI systems stack — setting a high bar for technical excellence, collaboration, and delivery
• Stay hands-on: contribute to system architecture, participate in code and design reviews, pair with engineers on complex problems, and own critical technical decisions for the team's most impactful systems
• Own the engineering roadmap for GTM AI systems — partnering with Sales Ops, BizTech, Finance, Legal, and GTM leadership to set priorities, define milestones, and communicate progress
• Drive delivery of AI-first GTM systems: agentic AI pipelines, LLM orchestration layers, Salesforce CPQ integrations, real-time Slack applications, and AWS event-driven architectures
• Champion engineering quality: establish and uphold standards for code review, testing, observability (distributed tracing, alerting, SLAs), incident response, and documentation
• Create a culture of responsible AI development — ensuring the team follows safe data handling practices, maintains audit trails, and builds human-in-the-loop controls from the start
• Manage team health: run effective 1:1s, give timely and actionable feedback, unblock engineers, resolve conflicts, and advocate for your team's needs within the broader org
• Identify and eliminate systemic sources of friction in GTM workflows — turning recurring manual processes into automated, self-healing systems that scale with the business
• Serve as a technical authority in cross-functional conversations — representing the engineering team's perspective to VP- and C-level GTM stakeholders
• 8+ years of software engineering experience, including 2+ years in an engineering management or tech lead role with direct reports
• Strong technical depth in Python (production services, async processing, LLM integration) and TypeScript/JavaScript (React, Node.js)
• Hands-on Salesforce platform experience: REST/Bulk/Streaming APIs, SOQL, CPQ/Steelbrick, platform events, and flow automation
• Solid AWS expertise: Lambda, SQS/SNS/EventBridge, API Gateway, S3, RDS/Aurora, CloudWatch, IAM, and multi-account patterns
• Experience building and deploying LLM-powered systems using OpenAI API, Anthropic API, LangChain, LangGraph, or equivalent agentic frameworks
• Demonstrated ability to lead multi-engineer technical efforts: writing design docs, running design reviews, and defining engineering standards
• Track record of effective people management: hiring, performance development, and building inclusive team culture
• Strong cross-functional communication skills — able to translate engineering decisions to non-technical business stakeholders
• Bachelor's degree in Computer Science, Engineering, or related field, or equivalent practical experience
• Experience designing and operating low-code automation platforms (Workato, MuleSoft, Salesforce Flow) alongside custom-built agentic systems
• Background in GTM engineering, RevOps tooling, or sales technology platform development in a high-growth B2B SaaS environment
• Familiarity with Model Context Protocol (MCP) or custom tool/function-calling patterns in production agentic systems
• AWS certifications: Solutions Architect Professional or DevOps Engineer Professional
• Experience operating in GovRAMP or FedRAMP-adjacent environments
• Prior experience scaling an engineering team through a period of significant organizational or technical growth