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Strong employer brand plus mid-level ML role but niche agentic focus reduces broad applicant pool.
Medium — core ML and cloud skills transferable, but agentic multi-agent specialization limits cross-industry fit.
Requires explicit 2+ years AI/ML experience and cloud/DevOps skills, so moderate filtering.
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Develop, integrate, and support multi-agent AI workflows and event-driven architectures within the agentic AI platform.
Collaborate with senior engineers to build agent workflows and platform components, utilizing agent frameworks like LangChain or GoogleADK.
Support deployment, monitoring, and troubleshooting of agentic AI services across cloud environments (AWS, GCP, Azure) and on-premises.
Bachelor’s degree in Computer Science, Engineering, or related field, or equivalent practical experience.
0–7 years of software engineering experience with at least 2 years exposure to AI/ML, distributed systems, or agent-based architectures.
Proficiency in Python and familiarity with at least one additional programming language (Java, Go, or C++).
Experience with event-driven architectures, REST/gRPC APIs, microservices, cloud application development (AWS, GCP, Azure), and basic DevOps practices including CI/CD and containerization (Docker/Kubernetes).
Early-career professional with demonstrated experience or coursework in multi-agent systems and agentic AI workflows.
Hands-on experience working in cloud-native environments and familiarity with agent orchestration tools and event-driven system designs.
Comfortable operating in collaborative agile teams with exposure to technical code reviews, testing, and cloud service monitoring.