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Strong employer brand plus mid-level seniority and sought-after AI skills increase competition for candidates.
Agentic ML platform and cloud expertise transfer across industries but require specific ML platform experience.
Explicit 5–10 years requirement plus mandatory agentic/ML, cloud, Kubernetes, and CI/CD skills raises strictness.
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Design, implement, and optimize complex agent orchestration and multi-agent workflows using frameworks like LangChain, Langraph, or GoogleADK.
Lead development and enhancements of event-driven architecture for assigned domains ensuring high availability and reliability.
Mentor junior engineers, drive platform improvements in deployment, monitoring, and incident response across hybrid multi-cloud environments (AWS, Google Cloud, Azure).
Bachelor's or Master's degree in Computer Science, Engineering, or related field.
5–10 years of hands-on experience designing, building, and deploying distributed or agentic systems.
Proficient in Python and familiar with at least one additional language (Java, Go, or C++).
Experience with event-driven, microservices, or multi-agent architectures and cloud-native development on AWS, Google Cloud, and/or Azure.
Experienced in independently driving complex agentic AI platform projects in cross-functional and hybrid cloud environments.
Strong leadership skills demonstrated by mentoring senior associates and leading architecture development.
Practiced in implementing scalable event-driven and multi-agent systems with deep familiarity of cloud-native operations and CI/CD pipelines.