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Strong employer brand, metro location, and mid-level ML role balanced by niche agentic AI specialization.
Highly specialized agentic AI and multi-agent engineering implies limited cross-industry transferability.
Explicit 5–10 years, required cloud, multi-agent, and runtime engineering skills enforce strict filters.
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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 architectures; maintain runtime components with high availability and reliability.
Drive improvements in deployment, monitoring, and incident response across AWS, Google Cloud, and Azure; mentor junior engineers and collaborate cross-functionally.
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
5–10 years of experience designing, building, and deploying distributed or agentic systems.
Proficiency in Python and familiarity with at least one of Java, Go, or C++.
Experience with event-driven/microservices architectures, cloud-native development on AWS/Google Cloud/Azure, CI/CD, Kubernetes, and software testing.
Mid-career engineer capable of independent design and operational ownership of agentic AI systems.
Experienced in advanced event-driven and multi-agent architectures at scale with cloud-native operations across multiple clouds.
Demonstrated ability to lead technical mentorship and cross-team collaboration within agile environments.