• Design & Build AI-Powered Features: Architect, implement, and ship data-driven product features, always starting with the customer problem first. From prototyping through production, you’ll apply the right level of technology (whether simple heuristics or advanced AI) to deliver impact. • Build for Production: Build maintainable and scalable systems, including writing clean, testable code, integrating with new and existing data pipelines, and deploying solutions and services into cloud environments. • End to End Solution Delivery: Operate as an end-to-end developer in a fast paced startup. This involves identifying opportunities, prototyping solutions, securing stakeholder support, and productionalizing features that deliver measurable business value. • Applied AI Innovation: Research and apply modern methods (AI agents, LLMs, RAG, embeddings, supervised/unsupervised learning) to power new product capabilities, prioritizing impact and speed over perfection. • Enhance User Experience Through AI: Translate business problems into AI solutions that improve user workflows, accelerate insights, and drive measurable value. • Collaborate Cross-Functionally: Work with business stakeholders and other engineers to turn customer problems into technical requirements and impactful features. • Promote Best Practices: Establish and evangelize standards for AI/ML engineering and data quality across the team.

• Play a core role in helping to design and develop new database capabilities, including analytics, clustering and distributed operations, query and storage optimizations, and more. • Develop, test, and release new features and functionality from our database technical roadmap. • Continually improve, optimize, and test the existing functionality of TimescaleDB. • Improve infrastructure to evaluate and test database correctness and performance. • Work closely with our Cloud Engineering team to build a world-class experience for our TigerData customers. • Provide elevated technical assistance to high-value customers, gaining insight into the needs and experiences of our users. • Be an enthusiastic and personable teammate, receiving and providing code reviews and partnering and helping other engineers.

• Map GTM bottlenecks: Partner with RevOps, Sales, Marketing, and CS to identify where AI can reduce manual effort, increase speed, or improve targeting. • Prototype fast: Use GPT-4, Claude, Zapier, Clay, Hex, Notion, and similar tools to quickly ship working workflows. • Run pilots: Deploy in-field with SDRs, AEs, and CSMs. Shadow, iterate, and learn. • Measure ROI: Quantify hours saved, pipeline influenced, and conversion lifts. • Operationalize workflows: Document and transition working flows to GTM Systems, Enablement, or Marketing Ops for scale. • Translate GTM strategy into execution: Operationalize Piper artifacts into real-time workflows that drive pipeline growth and faster prospect follow-up. • Deploy self-serve AI tools: Launch Slack-triggered workflows that reduce prep/admin time by 25–40% and dynamically prioritize accounts. • Automate connected workflows: Improve hand-offs across Salesforce, Salesloft, Gong, and G2 Intent, cutting time-to-action by 20–30%. • Partner across functions: Increase adoption of GTM tools by 60–80% by aligning AI workflows with how reps and CSMs actually work. • Benchmark against best-in-class: Build internal orchestration modeled on leading GTM platforms like Qualified.

• Creating the most compelling experience for users to explore and manage their multimodal data. • Closely working with the rest of the team and designers to optimize user experience. • Building scalable backends for LanceDB Cloud that offer a serverless experience for billion-scale datasets. • Fast pace with a stellar team of core contributors to incredible projects like Python Pandas, Arrow, Delta-rs, Hadoop, to define the next generation data system for AI. • Future leadership opportunities as the team grows. • Be the driving force to raise the bar and strive for better architecture and best practices within the company.