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Niche agentic AI skillset lowers supply, but mid-level experience range and known firm increase competition.
Specialized agentic AI, multi-agent and cloud skills moderately limit transferability from non-ML backgrounds.
Explicit 2+ years AI/ML exposure, Python, cloud and DevOps familiarity create moderate screening filters.
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Develop and integrate multi-agent workflows and platform components under guidance of senior AI engineers.
Build and assist in event-driven processes for scalable agentic AI systems on cloud platforms (AWS, GCP, Azure).
Support deployment, testing, monitoring, and troubleshooting of agentic AI services in cloud and on-prem environments.
Bachelor’s degree in Computer Science, Engineering, or related field, or equivalent practical experience.
0–7 years of overall software engineering experience with at least 2 years in AI/ML, distributed systems, or agent-based architectures.
Proficiency in Python plus familiarity with another language (Java, Go, or C++).
Experience with event-driven architectures, REST/gRPC APIs, microservices, cloud application development (AWS, GCP, or Azure), and basic DevOps practices including CI/CD and containerization (Docker/Kubernetes).
Early-career professional with hands-on experience building agentic AI workflows using frameworks like LangChain, Langraph, or GoogleADK.
Comfortable working collaboratively with senior engineers in agile team environments including code reviews and sprint planning.
Technical focus on developing and supporting multi-agent AI systems and event-driven architectures in cloud and on-prem settings.