• Design and implement AI-powered features: integrate LLM and build AI agents. • Design and implement end-to-end (frontend and backend) non-AI features, services and business logic that make the solution complete. • Build and maintain MCP servers to expose domain data and capabilities as tools for AI agents. • Implement RAG workflows to ground LLM responses in factual data using embeddings, chunking and vector databases. • Instrument and optimize OpenAI integrations for cost, latency, and accuracy in production environments. • Collaborate with product, design and architecture teams to craft exceptional user experiences built on AI. • Participate in technical design reviews, shaping architectural decisions and engineering standards.

• Design Tilt’s future operating systems: Partner with senior leaders to diagnose current pain points and co-design AI-first processes and systems that scale with the business. • Shape the “agentic” operating model: Define how Tilt integrates autonomous tools, human judgment, and systemized knowledge into everyday decision-making. • Drive measurable outcomes: Deliver technical and analytical projects that unlock speed, reduce manual effort, and increase team capacity. • Lead proof-of-concepts: Prototype and validate redesigned processes using tools like Claude, N8N, and custom GPTs/skills. Drive • Translate innovation into scale: Convert proof-of-concept learnings into scalable frameworks and playbooks that can be applied across functions. • Enable technical transformation: Collaborate with data and engineering partners to ensure our infrastructure supports demand for agentic capabilities. • Advise leadership: Act as a trusted advisor to the CEO, Head of Product, and senior leaders, aligning AI capabilities with business priorities. • Champion cultural change: Promote new ways of working that preserve Tilt’s culture of ownership while accelerating responsible AI adoption.

• Identifying inefficiencies across Sales, Marketing, and RevOps and proactively fixing them • Building and shipping AI-powered workflows, tools, and MVPs (internal-first, occasionally customer-facing) • Automating repetitive GTM processes (lead enrichment, outbound personalization, CRM workflows, routing, etc.) • Rapid experimentation: going from idea → prototype → live usage in days, not weeks • Partnering across teams to deeply understand problems and deliver solutions that actually get used • Acting as an internal thought partner on how AI can transform our GTM motion • Continuously exploring new AI tools, workflows, and ideas and bringing the best ones into the company • **Shipping is the goal, not prototypes that never get used**

• Lead engineering for AI initiatives • Architect the stack and prompt engineer LLMs • Collaborate with product managers, designers, and engineers • Mentor other engineers and conduct hiring