• Design and implement safety, isolation, and governance controls for agents running in production • Build orchestration pipelines using n8n,LangGraph, or similar frameworks • Create reusable automation patterns that other teams can adopt without your direct involvement • Rapidly prototype AI solutions for business processes (support triage, document processing, configuration automation, SDLC workflows) • Write effective prompts and prompt chains for complex multi-step tasks • Optimize for cost, latency, and accuracy across LLM providers • Contribute to the AI-augmented SDLC: coding assistants, automated testing, deployment automation, ticket quality validation • Hand off completed skills and automations to non-technical operators with clear documentation • Perform other duties as assigned

• Design, develop, and maintain robust, scalable, and secure full-stack web applications. • Build intuitive and responsive user interfaces using JavaScript frameworks. • Develop server-side logic, APIs, and database interactions using Java, PHP, and SQL. • Create, maintain, and optimize front-end components using HTML, JavaScript, jQuery, and CSS frameworks (e.g., Tailwind, Bootstrap). • Write scripts and integrate with back-end processes where the GUI acts as a wrapper to bash scripts. • Ensure code quality through proper testing, debugging, and adherence to coding standards. • Integrate third-party libraries, APIs, and systems into the application. • Maintain and enhance existing applications, ensuring compatibility with evolving technologies. • Monitor application performance and troubleshoot issues to ensure optimal functionality. • Collaborate with product managers, designers, and stakeholders to translate business requirements into technical specifications. • Work closely with cross-functional teams, including UI/UX designers, QA engineers, and DevOps teams.

• Lead the design and architecture of enterprise-level Java applications, ensuring scalability, maintainability, and performance. • Provide technical leadership and mentorship to development teams, promoting adherence to design patterns and coding standards. • Conduct performance tuning and optimization of applications to meet or exceed performance benchmarks. • Collaborate with product managers, QA, and other stakeholders to define technical requirements and project timelines. • Develop and maintain shell scripts to automate deployment, monitoring, and other operational tasks. • Review and improve existing codebases, including Hibernate integration and database interaction layers. • Facilitate technical discussions and decision-making processes to resolve complex design and implementation challenges. • Oversee level design aspects where applicable, ensuring alignment with overall application architecture.

• Build AI-powered internal tools that compress the work of the GTM team. Lead enrichment and scoring agents, account research workflows, automated outbound personalization, call summarization and insight extraction, internal knowledge agents over Slack, Notion, and the CRM. Think about every hour of repetitive GTM work as a candidate for automation. • Build customer-facing growth surfaces. Interactive demos, sandboxed playgrounds, in-product guides, AI-assisted onboarding, dynamic case study experiences, and tools that help prospects evaluate Goldsky themselves before they ever talk to sales. • Ship marketing engineering. The website, landing pages, A/B tests, lifecycle email flows, attribution plumbing, and the integrations between marketing tools, CRM, and product analytics. Treat the GTM stack as a real engineering surface, not a pile of duct tape. • Partner with sales engineering and solutions to automate parts of the customer evaluation journey: provisioning, sample pipelines, integration accelerators, ROI calculators, technical content generation. • Instrument and learn. Set up the analytics and experimentation needed to know which tools and surfaces are actually driving growth. Kill what doesn’t work, double down on what does. • Be the AI specialist for GTM. Stay close to the frontier of LLMs, agent frameworks, and AI-native tools, and bring back the ones that meaningfully change how we operate. Help the rest of the company become better AI users.