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Medium—specialized agentic AI skillset reduces applicants despite State Street brand and mid-level seniority.
Medium—agentic AI and cloud SRE skills are transferable across industries but require ML-specific experience.
High—explicit 5–10 years requirement plus mandatory agentic AI, cloud, and Kubernetes expertise.
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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 and oversee runtime components to maintain high availability and reliability.
Mentor junior engineers, drive improvements in deployment and monitoring across hybrid multi-cloud environments (AWS, Google Cloud, Azure), and collaborate cross-functionally.
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.
Proficiency in Python plus familiarity with at least one modern programming language (Java, Go, or C++).
Experience with event-driven, microservices, or multi-agent architectures, cloud-native development (AWS, Google Cloud, Azure), CI/CD, Kubernetes, and software testing.
Experienced mid-career engineer capable of independently handling complex agentic AI platform tasks and leading architectural enhancements.
Operates effectively in hybrid and multi-cloud DevOps environments, driving high availability and scalable solutions.
Strong mentoring skills with ability to lead knowledge sharing in a collaborative, cross-team setting.