Software Engineering Manager (Agentic AI)

Join Tulip, a leading company in the AI-driven development space. As a Software Engineering Manager, you will lead the engineering team in building Tulip's new agent-native app-building product. You will own the technical architecture and delivery of the product, hire and mentor a senior team, establish engineering standards, and collaborate with product and design teams. This role offers a flexible work environment, unlimited vacation policy, and competitive benefits.

• Lead the engineering team in building Tulip’s new agent-native app-building product, overseeing technical architecture and delivery.
• Hire, mentor, and grow a senior engineering team, establishing engineering standards and fostering an AI-first development culture.
• Collaborate with product, design, and other engineering teams to deliver features end-to-end, ensuring alignment with business goals.
• You possess high levels of technical acumen, people management skills, and a keen desire to deeply understand the business value of what you’re building. You’ve honed your technical skills through years of building and delivering SaaS products, and you’re now energized by the chance to build at the edge of what AI models can do
• You’re passionate about mentoring engineers and helping them grow, and you bring strong opinions about agent architectures, context management, and building scalable systems. You’re a collaborative, motivated self-starter who leads from the front and brings your authentic self to work
• Cross-functional leadership with product, design, and customer-facing teams to deliver features end-to-end
• Experience building and scaling large SaaS products and complex distributed systems
• 2-3+ years of experience leading software development teams with strong hands-on technical leadership, architecting solutions, and staying close to the code
• Strong product-engineering instincts: you can prototype quickly, prune scope, and decide what to ship versus what to throw away
• Experience in building and scaling AI systems in production, including LLM fine-tuning and evaluation, agent orchestration and context management, retrieval pipelines and vector stores, tool invocation and MCPs, guardrails and safety layers, and end-to-end observability for non-deterministic systems
• Expertise in contemporary tech stacks including React, Node.js, MongoDB, and Postgres, with experience deploying in multi-cloud and multi-tenant environments
• Hands-on experience architecting systems that integrate agentic and generative AI capabilities, including tool use, context management, sandboxed execution, and long-running workflows