• Design, build, and operate backend services in Python that power AI-driven products and shared capabilities. • Build and maintain resilient service integrations across internal and external systems, handling failure modes, rate limits, and interface changes. • Own ambiguous, end-to-end problems: from early design and architecture through implementation, rollout, and iteration in production. • Develop and evolve LLM-backed features and agentic workflows used in production, with a focus on reliability, observability, and real-world behavior. • Contribute to core AI platforms and enablement systems—services that your team uses directly and that other engineers can build on. • Collaborate with product managers, researchers, and other engineers across teams to turn loosely defined AI use cases into concrete, production-ready systems. • Help shape evaluation and quality strategies for AI-powered features, including building or extending evaluation harnesses, benchmarks, or feedback loops. • Act as a technical leader for the work you own—making sound design decisions, coordinating with stakeholders, and contributing to design and code reviews.

• Design and implement tools, frameworks, and processes that enhance developer productivity and streamline the software development lifecycle • Integrate AI in all of our existing processes to make us faster and more agile • Architect solutions for breaking down monolithic systems into modular, maintainable services • Champion and implement AI-powered tools as productivity multipliers across engineering workflows • Define metrics and track improvements in engineering efficiency, cycle time, and developer experience • Build consensus around engineering standards and best practices that can be adopted company-wide • Collaborate with engineering leaders to identify bottlenecks in development workflows and implement solutions • Proactively identify opportunities for improvement in developer experience without waiting for direction • Evangelize engineering experience improvements and share success metrics with the broader organization • Mentor other engineers on software architecture, system design, and development best practices

• Design and implement tools, frameworks, and processes that enhance developer productivity and streamline the software development lifecycle • Integrate AI in all of our existing processes to make us faster and more agile • Architect solutions for breaking down monolithic systems into modular, maintainable services • Champion and implement AI-powered tools as productivity multipliers across engineering workflows • Define metrics and track improvements in engineering efficiency, cycle time, and developer experience • Build consensus around engineering standards and best practices that can be adopted company-wide • Collaborate with engineering leaders to identify bottlenecks in development workflows and implement solutions • Proactively identify opportunities for improvement in developer experience without waiting for direction • Evangelize engineering experience improvements and share success metrics with the broader organization • Mentor other engineers on software architecture, system design, and development best practices

• Own end-to-end campaign execution for the lender business in HubSpot, including email, lifecycle, nurture, paid ads, routing, and lead management programs • Build, launch, measure, and optimize campaigns based on performance and pipeline impact • Own day-to-day operation and optimization of the GTM tech stack (HubSpot, Clay, AirOps, Lemlist) • Build and maintain lead scoring models, routing logic, lifecycle stages, and SLAs • Ensure data quality, attribution accuracy, and system reliability across GTM systems • Partner closely with Marketing, Sales and Product Marketing to operationalize GTM strategy into execution • Design, improve, build and maintain automated workflows using tools like n8n, Lemlist, Clay, and AirOps • Build AI-powered enrichment, outbound, and intent-detection pipelines • Integrate GTM tools and data sources via APIs and automation platforms • Replace manual, repetitive processes with scalable, reliable workflows • Own marketing attribution, pipeline analytics, and GTM performance reporting • Build and maintain dashboards and automated reporting pipelines (Salesforce, HubSpot, Sheets, Looker or similar) • Create playbooks, SOPs, and documentation for GTM systems, campaigns, and workflows • Train and enable Marketing and Revenue teams on tools, processes, and best practices • Establish guardrails and operating models to ensure adoption, consistency, and trust in GTM systems