Put security first: Build and ship solutions that meet enterprise security standards (threat modeling, secure coding, privacy, and compliance) from design through production. Translate business needs into technical solutions: Partner with stakeholders to define problem statements, success metrics, and architectural approaches that deliver measurable outcomes. Design and lead architecture: Own end-to-end system design for cloud and AI workloads, making sound tradeoffs across reliability, performance, cost, and maintainability. Deliver quickly without sacrificing quality: Use modern engineering practices (CI/CD, automated testing, observability, and progressive delivery) to iterate fast and reduce operational risk. Drive customer success and adoption: Work directly with customer engineering teams to deliver production-ready solutions, unblock delivery, and ensure outcomes are adopted at scale. Build reusable, scalable assets: Create solution accelerators, reference architectures, and code that can be reused across customers and scenarios to maximize impact. Operate effectively in ambiguity: Continuously learn and adapt as technologies and customer priorities evolve; bring clarity, structure, and momentum to complex engagements. Lead and mentor across disciplines: Provide technical direction, coach engineers, and collaborate with product, data, and security partners to deliver as one team. Lead complex delivery end-to-end: Coordinate multiple workstreams, manage dependencies, and raise the bar on reliability and operational excellence for services running in production. Model inclusive, customer-obsessed leadership: Create an environment of trust, accountability, and continuous improvement while representing the company professionally with external stakeholders. Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience. Experience partnering directly with customers or internal stakeholders to deliver solutions end-to-end. Experience designing, deploying, and operating AI or LLM-based solutions, including prompt engineering, retrieval-augmented approaches, model tuning, evaluation, data quality, performance monitoring, and use of cloud AI platforms Familiarity with deploying and operating AI systems in production environments Comfortable with travel at 25%
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