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Global employer and metro mid-level ML role increase competition, while niche Agentic AI skills moderate applicant density.
Specialized Agentic AI, enterprise connector, and cloud/MLOps experience moderately restricts cross-industry transferability.
Explicit 5-7 years plus 1-2 years GenAI hands-on and specific tech stack requirements increase shortlisting strictness.
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Lead technical enablement, integration, and continuous enhancement of advanced agentic AI platforms and workflows.
Design, develop, and rigorously test custom connectors, APIs, and orchestrate complex agent workflows for enterprise AI solutions.
Optimize performance, maintain platform lifecycle including bug fixes, security patches, capacity planning, and provide expert-level troubleshooting and support.
Bachelor's or Master's degree required.
5-7 years total experience including 1-2 years hands-on with Generative AI and Agentic AI technologies/platforms (e.g., LangChain, LlamaIndex).
Proficiency in Python, Java, or Go; experience with API design/integration (REST, GraphQL, gRPC); enterprise integrations like Salesforce, SAP, ServiceNow.
Experience with Agentic AI frameworks, multi-agent orchestration, Google Cloud Platform (preferred), and monitoring tools (e.g., Prometheus, Grafana).
Experienced ML engineer with strong focus on Generative and Agentic AI operationalization and integration at enterprise scale.
Capable of designing scalable, secure AI workflows and connectors, with expertise in cloud environments, especially GCP and Vertex AI.
Demonstrates leadership potential and ability to mentor junior engineers, collaborate cross-functionally, and drive technical best practices.