• Learn what the role of Software Engineer entails at a fast-growing startup • Gain experience with technologies including: PHP, MySQL, Laravel, React, Javascript, GitHub, AWS, automated testing, RESTful APIs, Linux, etc • Work in a team to deliver an actual feature to production for our customers

• Lead the architecture and evolve a universal, relationship-centric catalog, focusing on entity modeling, typed relationships, and a canonical inventory graph. • Work closely with product managers and customers to define the technical strategy and roadmap for data discovery and governance at Netflix. • Act as a liaison between Data Platform and other organizations to build a cohesive Metadata Strategy across Netflix as we expand beyond streaming into Live, Ads and Games. • Champion data quality and governance by building validation engines, rules platforms, and automated health checks to ensure metadata completeness, freshness, and compliance. • Mentor and empower senior engineers and cross-functional partners, fostering strong technical decision-making and a culture of shared ownership. • Model operational excellence by driving improvements in reliability, incident response, and long-term operational best practices. • Stay ahead of industry trends in metadata management, graph technologies, and compliance, guiding build-vs-buy and technology adoption decisions. • Measure impact via adoption, data health metrics, onboarding speed, and downstream business enablement. • Exemplify and hold others accountable for demonstrating Netflix’s culture.

• Lead the design, documentation, and communication of end-to-end system architectures that align with Ozmo's strategic goals, including AI-first capabilities that handle non-deterministic outputs, continuous evaluation, and graceful fallbacks. • Architect scalable AI inference and retrieval stacks (vector/graph stores, embedding pipelines, RAG systems, caching, batching, streaming), balancing accuracy, cost, and latency targets. • Define and own architectural standards for AI-enabled systems, including agent orchestration, memory/state management, guardrails, model versioning, evaluation gates, and safe rollout practices. • Architect multi-tenant AI patterns across the platform, including per-customer data isolation, access control, model configuration, data residency, and cost allocation. • Collaborate with customers' technical teams to evaluate requirements, architect integrations, and ensure seamless deployment aligned with their existing systems. • Partner with product, data, ML, and engineering leaders to translate AI opportunities into deployable system designs; guide tradeoffs between deterministic services and model-driven components. • Create reusable reference architectures and "golden paths" for teams shipping AI features, accelerating delivery while maintaining quality standards. • Mentor engineers and foster a culture of innovation, experimentation, and technical excellence. • Ensure AI systems adhere to Ozmo’s reliability, security, and compliance requirements, including PII handling, policy enforcement, auditability, and incident response for AI components. • Contribute to long-term technical roadmaps and architectural reviews that include AI-first design principles.

• Design and maintain pre-sale GTM workflows in Salesforce, including routing, scoring, qualification, handoffs, and deal support. • Partner with Marketing Operations to implement lead management and enrichment workflows in Salesforce—including lifecycle state, enrichment timing, routing impact, and data quality checks—so GTM teams operate on accurate, trusted data. • Partner closely with Marketing and Sales Operations to translate GTM processes and motions into scalable, inspectable workflows. • Configure Salesforce using Flows, custom objects, validation rules, reports, dashboards, and light development where appropriate. • Partner with the GTM Systems Architect to implement system designs and provide execution feedback that informs future architectural decisions. • Partner with the SFDC Systems Engineer on complex development, integrations, and platform-level changes. • Implement automation and AI-assisted workflows with appropriate guardrails and human-in-the-loop controls. • Reduce repetitive, manual GTM work by replacing it with durable, failure-resilient workflows. • Establish monitoring and validation mechanisms for high-impact GTM workflows. • Ensure Salesforce configurations remain secure, auditable, and reliable as volume and complexity grow. • Partner closely with the GTM Engineer (Post-Sale) to ensure clean handoffs, shared data models, and end-to-end lifecycle integrity.