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Tier-1 brand, mid-level ML title, metro hiring, and broad cloud/ML skillset increase competition.
Specialized agentic AI and cloud-runtime skills are transferable across sectors but favor AI-platform backgrounds.
Explicit 5–10 years requirement plus mandatory cloud, Kubernetes, and agentic frameworks makes filters strict.
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Design, implement, and optimize complex agent orchestration and multi-agent workflows using frameworks like LangChain, Langraph, or GoogleADK.
Lead event-driven architecture development and maintain runtime components ensuring high availability across hybrid and multi-cloud environments (AWS, Google Cloud, Azure).
Mentor junior engineers, conduct code reviews, and drive improvements in deployment, monitoring, and incident response processes.
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
5–10 years of hands-on experience in designing, building, and deploying distributed or agentic systems.
Proficient in Python and familiar with at least one additional modern programming language (Java, Go, or C++).
Experience with event-driven, microservices, or multi-agent architectures at scale; cloud-native development on AWS, Google Cloud, and/or Azure; CI/CD pipelines; container orchestration (Kubernetes).
Mid-career engineer capable of independently designing and executing agentic AI workflows with domain-specific framework integrations.
Experience leading architecture development and maintaining complex runtime systems in hybrid/multi-cloud environments.
Strong mentor and collaborator able to guide junior engineers and cross-functional teams on best practices and technical documentation.