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Metro hiring and a visible senior platform role increase competition, partially offset by niche agentic AI specialization.
Platform, Kubernetes, and Python skills transfer broadly, but agentic AI/MCP connector experience adds domain specificity.
Extensive mandatory tech stack and platform-operational expertise drive high shortlisting strictness.
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Integrate, deploy, and scale Cogentiq AI platform across enterprise environments, focusing on core, runtime, and governance layers.
Build and optimize AI agents and workflows, translating business problems into production-grade agentic solutions.
Drive platform adoption through onboarding and enablement of internal and customer teams while ensuring platform reliability and compliance.
Strong Python development skills with OOP and system design fundamentals.
Experience with FastAPI or equivalent backend frameworks.
Hands-on experience with Docker, Kubernetes, and CI/CD pipeline deployments.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in enterprise platform integration and backend API design using MCP-based connectors, SDKs, and storage/business application integrations.
Skilled in troubleshooting distributed systems with a focus on security, governance, and observability.
Proficient at translating complex business use cases into scalable technical agentic AI solutions.