Director, Engineering

• Develop a technical vision for engineering that ties directly to Sunday's business goals, and translate it into a 6–12 month roadmap built with Product and the Leadership Team
• Build and own Sunday's AI strategy for engineering, establish a consistent approach to AI-assisted and agentic development, and use it to help the team move faster and fail faster
• Serve as the connective layer between business/product priorities and the engineering team

• Push Sunday toward becoming a genuinely AI-native product company, not a deterministic product with a chatbot bolted on, but one where core functionality is LLM-driven where it makes sense
• Bring real excitement and a point of view about this shift, and get the team energized about building toward it together
• Support early agent-based project work and help set a broader, more consistent direction for how the team builds and evaluates agentic systems
• Establish evaluation practices (evals) for AI-driven functionality; fluency with eval tooling (e.g., Braintrust, Langfuse, or similar) is a strong plus, since non-deterministic, LLM-driven logic can't be tested the way traditional deterministic code is

• Bring maturity to foundational infrastructure and architecture decisions
• Identify and invest in the technical decisions that save the team time now, rather than accumulating further shortcuts
• Bring a builder's mindset to this work personally; this isn't a hands-off architecture review function; it's active, credible participation in solving it

• Own hiring strategy and interview process for both ICs and future managers, partnering closely with the People team; instill and maintain a high hiring bar
• Prevent single points of failure, put institutional knowledge, documentation, and cross-training in place
• Give engineers real paths to grow, including mentorship, stretch opportunities, and regular, honest development feedback

• Hold the team accountable to its own goals; regularly evaluate team structure and workflow to keep the org moving quickly
• Codify and disseminate engineering best practices, testing, code review, PR norms, and how those practices scale as AI-assisted development increases velocity, so speed doesn't outpace quality
• Own engineering metrics — delivery against roadmap, quality/bug backlog, system performance and uptime, and team velocity, and use them to surface bottlenecks to leadership
• Deliver honest, frequent, and respectful feedback, and build a culture where the team gives and receives it the same way

• Represent engineering as part of company leadership, communicate plans, tradeoffs, and challenges to other functional heads in terms the whole business can act on
• Act as a true product partner given how much of Sunday's product is (and will increasingly be) LLM-driven; engineering and product decisions are directly intertwined, not sequential handoffs
• Understand how product thinks, and bring engineering's perspective into product conversations early — this is a collaboration, not a request queue

• The team feels led, not managed, with clear priorities, cleared blockers, and visible follow-through
• Strong opinions, held loosely: you set direction but trust engineers to own execution
• The team has real conviction that engineering is heading in the right direction
• A working AI strategy the whole team is aligned on, with visible gains in velocity and quality

• Proven experience leading engineering at a small-to-mid-size or growth-stage company, with a track record of taking on increasing scope
• A genuine builder, you want to be hands-on writing code and shaping product, not solely managing people and process
• Strong individual technical credibility — you can go deep enough to earn trust with senior engineers, not just manage from a distance
• Direct experience with, or strong enthusiasm for, AI-native product development — building products where core functionality is LLM-driven rather than deterministic, not just adding an AI chat feature to an existing product
• Familiarity with LLM evaluation practices and tooling (Braintrust, Langfuse, or similar), given the shift toward non-deterministic, AI-driven functionality
• Front-end depth, or demonstrated ability to grow it across a team
• Hands-on familiarity with AI-assisted and agentic development workflows, and a clear point of view on how to scale them responsibly
• A naturally curious, learning-oriented mindset, hungry to keep growing and to bring the team along with you
• Experience building org structure, hiring processes, and team practices from a lighter-weight or informal state
• A true product-collaboration mindset: understands how product and engineering decisions shape each other, and doesn't need — or want — a roadmap simply handed to them
• A business-minded, collaborative style, comfortable building relationships across the whole company, not just within engineering
• Humility and directness, able to talk openly about mistakes and how they were resolved, and to give feedback as a gift
• A communicator who can move fluidly between technical depth and company-wide clarity

As a company rooted in nature, we deeply understand the benefits of diversity. We work to build a culture that attracts a diverse mix of talented people to help us bring lawn care out of the dark ages. We are committed to building a diverse, vibrant team that brings determination and passion to our work everyday.