• Ship customer-facing AI features across the full stack. Build the experience and what's behind it — LLM-backed flows, retrieval (RAG) and embeddings, and agentic tool-calling — through to a fast, accessible, well-crafted UI. • Treat AI output as something you verify, not assume. Build evaluations, guardrails, and monitoring into AI features so quality is measurable and holds up in production. • Sweat the front-end craft. • Stay close to customers. Join customer calls when more context is needed to design the right solution, participate in a support escalation rotation, and watch session recordings on the features you own. • Own outcomes, not just output. • Co-author the solution. PMs own strategy and sequencing; you bring the judgment and craft for how solutions actually get built. • Own production readiness from the start.

• design, build, deploy, and maintain complex full-stack features • own features from technical discovery through production and ongoing optimization • design scalable solutions across frontend, backend, APIs, databases, and cloud infrastructure • write clean, maintainable, and well-tested code while promoting best practices • partner closely with Product Managers, Designers, QA, and Engineers to translate business needs into scalable technical solutions • improve application performance, scalability, observability, and production reliability • mentor other engineers through code reviews, knowledge sharing, and technical guidance • contribute to both automated and manual testing practices

• Design, implement, and maintain CI/CD pipelines and environment automation using Jenkins, GitHub Actions, Terraform, and Ansible • Manage and operate AEM as a Cloud Service environments including provisioning, configuration, deployment, and troubleshooting • Configure, monitor, and support Apache web servers and AEM Dispatcher setups • Build and manage containerized services using Docker and Kubernetes across development, staging, and production • Guide internal and external teams on performance optimization and operational best practices for AEM • Lead infrastructure builds for high-availability production environments on AWS, GCP, or Azure • Automate operational tasks and enhance deployment workflows using Bash, Python, and Groovy • Monitor site uptime and performance using tools like New Relic, Datadog, and Splunk • Maintain operational documentation including DR runbooks and infrastructure diagrams • Participate in incident response and on-call support rotation

• Professional responsible for technically leading the evolution of the CRM Platform, serving as a reference in data architecture and integrations, with a strong understanding of the business. • Must support the team in technical decisions, ensure engineering best practices, and enable scalable, reliable solutions aligned with the company’s strategy. • Works closely with stakeholders, translating business needs into efficient technical solutions.