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Metro location, hybrid flexibility, and broad full-stack plus AI skillset raise applicant competition.
Role demands specialized AI platform, ML systems, and PhD-level expertise, limiting cross-industry transferability.
Explicit 10+ years, PhD/Master's from Tier I, and specific tech/AI requirements make filters strict.
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Architect, design, and lead development of scalable, secure, maintainable AI platform components across full stack including frontend, backend, infrastructure, and platform services.
Own technical direction and solve complex engineering challenges from concept through deployment and continuous iteration, ensuring system reliability, performance, and scalability.
Collaborate with engineering, ML, data science, and product teams to integrate AI capabilities into production-ready systems and provide technical mentorship across the organization.
PhD in Computer Science, Artificial Intelligence, Machine Learning, or related field; alternatively Master's from Tier I institution.
10+ years of software engineering experience with strong expertise in scalable production system and platform design.
Proficiency in frontend technologies (React, TypeScript) and backend languages (Python, Go), plus experience with cloud platforms (AWS, GCP, or Azure), Docker, Kubernetes.
Strong understanding of system design, distributed systems, API architectures (REST, GraphQL), CI/CD, observability, security, reliability, and production operations.
Experienced technical leader capable of owning complex, high-impact engineering initiatives end-to-end in AI-driven environments.
Deep domain experience integrating AI/ML systems, AI agents, or language models into scalable production platforms.
Strategic thinker with strong systems design skills, able to lead architecture discussions and elevate engineering standards across multidisciplinary teams.