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Niche agentic AI specialization reduces applicant density despite metro location and 2–7 year mid-level window.
Agentic AI, multi-agent frameworks, and ML/cloud experience limit industry portability, increasing domain specificity.
Explicit 2+ years AI exposure plus mandatory Python, cloud, and DevOps basics impose moderate screening.
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Develop, integrate, and support multi-agent workflows and event-driven architectures within the agentic AI platform.
Collaborate with senior engineers to design and build agent workflows and platform components using frameworks like LangChain, Langraph, or GoogleADK.
Support deployment, monitoring, and troubleshooting of agentic AI services in cloud (AWS, GCP, Azure) and on-premise environments.
Bachelor’s degree in Computer Science, Engineering, or related field, or equivalent practical experience.
0–7 years in software engineering, with at least 2 years exposure to AI/ML, distributed systems, or agent-based architectures.
Proficient in Python plus familiarity with another modern language (Java, Go, C++).
Experience with event-driven architectures, REST/gRPC APIs, microservices, cloud application development (AWS, Google Cloud, Azure), and basic DevOps practices (CI/CD, Docker/Kubernetes).
Early-career professional comfortable working closely with senior engineers and participating in collaborative development processes.
Experience or coursework involving multi-agent systems or agentic AI workflows indicating domain interest and foundational knowledge.
Familiar with cloud environments and modern software engineering practices including testing, deployment, and monitoring of scalable distributed systems.