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Tier-1 employer and metro Bangalore plus mid-seniority increase competition despite niche agentic AI requirement.
Agentic AI and multi-agent specialization increases domain specificity, though Python, cloud, and ML skills remain transferable.
Explicit 5–10 years plus mandatory agentic/ML expertise, cloud, Kubernetes, and CI/CD make shortlisting highly strict.
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Design and implement complex agentic AI workflows integrating frameworks like LangChain, Langraph, or GoogleADK to meet domain-specific needs.
Lead event-driven architecture development and drive improvements in deployment, monitoring, and incident response across hybrid and multi-cloud environments (AWS, Google Cloud, Azure).
Mentor junior engineers and collaborate cross-functionally with engineering, SRE, and product teams to advance the agentic AI platform and establish best practices.
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 additional modern programming language (Java, Go, or C++).
Experience with event-driven, microservices, or multi-agent architectures, cloud-native development and operations on AWS, Google Cloud, and/or Azure.
Mid-career engineer capable of independent design and implementation of advanced agentic AI systems and multi-agent orchestration.
Experienced leader familiar with event-driven architecture and hybrid multi-cloud environments, able to mentor and elevate junior engineers.
Strong collaborator comfortable working across engineering, SRE, and product teams to operationalize AI platforms and drive technical excellence.