Technologist, Data Analytics Engineering

Job Description Job Description Lead the architecture, engineering, and operationalization of enterprise AI platform capabilities, enabling secure, scalable, and reusable AI services across the organization. Own the productization of foundational AI capabilities—including AI Gateway, Semantic Layer, Agentic Harness, CLI tooling, and integration frameworks—to accelerate AI solution delivery and adoption. Key Responsibilities Define and implement the platform engineering strategy for AI services, including CI/CD, IaC, API lifecycle management, observability, security, governance, and multi-environment deployment patterns. Architect, build, and scale foundational AI capabilities (e.g., Semantic Layer, Agentic Harness, AI Gateway, orchestration frameworks, reusable SDKs/CLI tools) while establishing standards, reference architectures, and engineering best practices across teams. Qualifications Educational Background: Bachelor’s or Master’s degree in Computer Science, Data Sciences, or related fields. Professional Background: 10+ years of experience in platform engineering, cloud architecture, DevOps/SRE, or software engineering, with demonstrated expertise in building large-scale enterprise platforms and developer enablement capabilities. Deep expertise in CI/CD, Infrastructure as Code, cloud-native architectures, API platforms, security, and automation, with experience operationalizing AI/ML or GenAI platforms and services in enterprise environments. Preferred Skills: Certifications in Cloud Architecture Experience with Agentic frameworks Excellent communication and stakeholder management skills