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Known employer and metro location increase competition, but niche agentic AI specialization reduces applicant density.
Technical ML, multi-agent, and cloud skills are transferable, but finance domain experience moderately matters.
Explicit 5–10 years plus specialized agentic AI, cloud, and runtime requirements enforce strict filters.
Design, implement, and optimize complex agent orchestration and multi-agent workflows using frameworks like LangChain, Langraph, or Google ADK.
Lead development and enhancement of event-driven architecture and ensure high availability and reliability of runtime components.
Mentor junior engineers, drive best practices adoption for cloud-native deployments, and collaborate cross-functionally to accelerate innovation.
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 plus familiarity with at least one other modern programming language (Java, Go, or C++).
Experience with cloud-native development and operations on AWS, Google Cloud, and/or Azure, including CI/CD, Kubernetes, and monitoring solutions.
Experienced in event-driven, microservices, or multi-agent architectures at scale with a strong software engineering background.
Capable of independently owning complex technical solutions and leading engineering efforts in agentic AI platforms.
Skilled in mentoring and knowledge sharing within engineering teams and comfortable working in hybrid/multi-cloud environments.