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Metro location, mid-level experience range, and reputable employer create moderate applicant competition.
Specialized agentic AI, multi-agent frameworks, and runtime engineering require strong ML/AI domain experience.
Explicit 5–10 years plus mandatory cloud, Kubernetes, CI/CD, and agentic framework experience enforces strict filters.
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Design, implement, and optimize complex multi-agent workflows using frameworks like LangChain, LangGraph, or GoogleADK.
Lead event-driven architecture development, ensuring high availability and reliability of runtime components across hybrid multi-cloud environments (AWS, Google Cloud, Azure).
Mentor junior engineers and drive adoption of best practices for cloud-native agentic AI platform deployments.
Bachelor's or Master's degree in Computer Science, Engineering, or related field.
5 to 10 years of experience designing, building, and deploying distributed or agentic systems.
Proficiency in Python and at least one other modern programming language (e.g., Java, Go, C++).
Experience with event-driven architectures, microservices, cloud-native development (AWS, Google Cloud, Azure), CI/CD, container orchestration (Kubernetes), and software testing.
Experienced mid-career engineer comfortable leading complex agentic AI platform projects independently.
Strong operational focus on deployment, monitoring, and incident response in multi-cloud environments.
Skilled at cross-team collaboration and mentoring junior engineers within an agile software development context.