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Metro location, mid-level experience band, and a recognizable employer balanced by niche agentic-AI specialization yield medium competition.
Core ML, Python, and cloud skills transfer across industries, but agentic AI specialization creates moderate domain bias.
Multiple mandatory filters—2+ years AI exposure, Python, cloud, and agent-framework experience—make shortlisting strict (high).
Develop and integrate multi-agent AI workflows and platform components leveraging agent frameworks like LangChain or Google ADK.
Support event-driven architectures and scalable agentic AI systems across cloud platforms (AWS, GCP, Azure) including deployment, monitoring, and troubleshooting.
Contribute to code quality through unit/integration testing, code reviews, sprint planning, and technical documentation within the team.
Bachelor’s degree in Computer Science, Engineering, or related field, or equivalent experience.
0–7 years software engineering experience, with at least 2 years in AI/ML, distributed systems, or agent-based architectures.
Proficiency in Python and familiarity with at least one additional modern programming language (Java, Go, C++).
Experience with event-driven architectures, REST/gRPC APIs, microservices, cloud environments (AWS, GCP, or Azure), and basic DevOps practices including CI/CD and containerization (Docker/Kubernetes).
Experience working closely with senior engineers in AI or distributed systems projects focusing on multi-agent workflows.
Comfortable operating in cloud-native and event-driven architecture environments.
Demonstrated capability or project experience involving AI agent orchestration, runtime engineering, or related agentic AI platforms.