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Specialized agentic AI skills narrow pool, but popular AI role increases applicant interest.
Deep LLM/agent expertise and production Python skills make the role highly domain-specific.
Many mandatory technical must-haves (LangGraph, LLM integration, Python, DSA) enforce strict screening.
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Design and implement multi-agent AI workflows focusing on orchestration, context management, and LLM integration with reliable, efficient production systems.
Develop complex, stateful, resumable agent workflows including checkpoints, human-in-the-loop controls, and error handling for robust AI agent operation.
Collaborate with infrastructure teams on deployment and contribute to system quality through evaluation loops, verification patterns, and observability features.
Proven programming skills in Python 3.10+ with async and typing experience.
Strong data structures, algorithms, and problem-solving ability, ideally demonstrated through competitive programming or equivalent experience.
Bachelor’s or master’s degree in Computer Science or a related field from a reputable institution.
Experience in multi-agent system design and agent orchestration using LangGraph or similar frameworks; direct exposure to LLM integration and context engineering is required.
Deep technical expertise in agentic AI systems, with hands-on experience building multi-agent workflows and context management architectures.
Skilled in rigorous software engineering practices including code quality, debugging, and root cause analysis applied to complex AI systems.
Experienced collaborator capable of explaining technical concepts clearly to diverse stakeholders and contributing to shared engineering standards.