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Mid competition: mid-level experience and strong employer brand, offset by niche agentic AI specialization.
Medium: core ML, cloud, and orchestration skills transfer, but agentic AI specialization reduces portability.
High strictness: explicit 5–10 years plus mandatory cloud, Kubernetes, CI/CD, and agentic ML engineering requirements.
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Design, implement, and optimize complex agent orchestration and multi-agent workflows using frameworks like LangChain and Google ADK.
Lead development and enhancements of event-driven architectures, ensuring high availability and reliability in 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.
Proficiency in Python and familiarity with at least one other modern programming 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 leading technical design and implementation of agentic AI or distributed systems with measurable impact.
Skilled in operating within hybrid/multi-cloud environments with strong runtime engineering and SRE practices.
Demonstrated ability to mentor engineers and collaborate across cross-functional teams for platform advancement and innovation.