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Senior, niche cloud+AI architect reduces mass applicant competition relative to mid-level generalist roles.
Requires specific cloud, PySpark/Databricks and agentic-AI experience, making skills less transferable across industries.
Explicit 10+ years, 4+ years leadership, and mandatory cloud, Databricks and agent experience create strict filters.
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Own and set the technical direction for enterprise agentic AI solutions across full-stack, cloud, data, and AI layers by leading and mentoring the engineering team.
Establish engineering standards, reusable deployment assets, and build deployment capabilities including reference architecture, IaC modules, and runbooks to reduce deployment dependencies on individuals.
Lead technical reviews, design walkthroughs, mentor Forward Deployed Engineers (FDEs) to independence, and act as final escalation for deployment and production issues.
10+ years in software, platform, or applied AI engineering with at least 4+ years leading engineering teams and delivering systems in production.
Technical expertise in Python, JavaScript/TypeScript front ends, relational and NoSQL databases, PySpark, Databricks, agent development with orchestration frameworks, and CI/CD & DevOps practices.
Hands-on architecture experience with cloud (specifically Azure) and security to own and defend decisions with client teams.
Work Experience Required: 10+ years; Notice Period: Not explicitly mentioned in the JD.
Experienced leader who influences through setting standards, mentoring, and building team deployment independence rather than individual delivery.
Strong strategic focus on scalable engineering capability with expertise spanning full-stack development, cloud architecture, data engineering, and AI/agent orchestration.
Comfortable owning complex cloud and AI system architectures, performing selective hands-on technical work to unblock teams, and managing stakeholder expectations and security reviews.