• GTM Architecture & Strategy Translate business goals into scalable GTM architecture: ICP definition, TAM modeling, segmentation logic, scoring models, automation workflows. • Build multi-channel GTM plans spanning ABM, outbound, paid/organic acquisition, retargeting, nurture, and partner-platform plays. • Design demand-generation “engines” rather than one-off campaigns — systems that can be reused, scaled, and adapted across ICPs and platforms. • Own marketing budget for demand gen experiments and ROI optimization, Data, Automation & Tech Stack Ownership. • Manage and integrate the full martech stack: HubSpot, Clay/enrichment tools, GA4, session / behavior analytics (Clarity or similar), ad/retargeting platforms, CRM integrations. • Build data pipelines and enrichment flows — tech-stack signals, hiring signals, funding signals — to power smart segmentation and account scoring. • Define and implement lead scoring, routing, lifecycle automation, attribution, and handoff processes to Sales. Maintain data hygiene, automation integrity, and scalability. • Launch and execute demand generation campaigns (ABM, nurture, retargeting, outbound) end-to-end. • Use automation and personalization at scale while preserving human-quality messaging. Rapidly iterate campaigns based on data, feedback, and performance — treat campaigns as experiments. • Build dashboards and reporting across funnel stages: reach → engagement → MQL → SQL → Opportunity → Close. Run CRO experiments, analyze behavior data (heatmaps, session recordings, conversions) and implement iterative improvements. • Use data to diagnose drop-offs, optimize flows, improve conversion, and reduce acquisition cost. Growth Loop Creation & Scaling Design and build scalable demand engines: once a blueprint works, replicate across ICPs, industries, and platforms. • Collaborate with Customer Marketing, Platform teams, Sales to pull in proofs (case studies, successes) and push them into the GTM engine for amplification. • Continuously refine ICP definitions, signal-based targeting, and feedback loops for smarter growth cycles. • Leverage AI tools (LLMs, custom GPTs, automation agents) to accelerate segmentation, content generation, personalization, analysis, and reporting. • Build AI-assisted workflows and make intelligent use of automation without compromising quality or brand voice.

• Develop, test, and maintain web applications, ensuring high performance and scalability. • Collaborate with product managers, designers, and developers to deliver features that meet user needs. • Write clean, maintainable, and scalable code following best practices. • Design and build secure RESTful APIs for web and mobile apps. • Ensure applications are responsive, optimized for mobile, and deliver consistent performance across devices. • Debug and fix application issues to improve reliability and performance. • Participate in code reviews to maintain high-quality standards and support team improvement. • Stay updated on industry trends, implement security measures, and find ways to enhance tools and processes for better productivity and performance.

• Configure, optimize, and maintain Sentry error monitoring across our application stack • Monitor, triage, and resolve production issues reported through Sentry • Investigate root causes of errors and implement sustainable fixes • Develop and maintain an AI-powered agent to automatically propose resolutions for common error patterns • Collaborate with development teams to improve error handling and logging practices • Create documentation and runbooks for error resolution procedures • Work closely with quality assurance and technical support teams to improve overall system reliability

• Design and build scalable and robust tools required for both internal and external use by machine learning, engineering and data teams • These tools will be used for data collection, testing, analytics and data management