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Tier-1 brand, mid-level seniority, and metro hiring increase competition but niche agentic AI specialization reduces it.
Agentic AI and multi-agent systems are specialized but skills remain moderately transferable across ML/AI roles and industries.
Explicit 6+ years, 2+ years AI exposure, cloud and tech stack requirements create strict filters.
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Develop, integrate, and support multi-agent workflows and event-driven architectures for the agentic AI platform.
Collaborate with senior AI engineers to design and build agent workflows and platform components using at least one agent framework such as LangChain or GoogleADK.
Deploy, monitor, troubleshoot, and maintain agentic AI services in cloud (AWS, Google Cloud, Azure) and on-prem environments.
Bachelor’s degree in Computer Science, Engineering, or related field (or equivalent experience).
6+ years software engineering experience, including at least 2 years in AI/ML, distributed systems, or agent-based architectures.
Proficient in Python plus familiarity with one other modern programming language (Java, Go, or C++).
Experience with event-driven architectures, REST/gRPC APIs, microservices, cloud development (AWS, GCP, or Azure), and basic DevOps practices (CI/CD, Docker/Kubernetes).
Experienced in designing and building scalable agentic AI workflows and event-driven systems using frameworks like LangChain or GoogleADK.
Strong operational and troubleshooting skills for cloud and on-prem deployment environments.
Ability to contribute in agile team settings via code reviews, sprint planning, and technical documentation.