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Tier-1 brand and mid-level experience increase applicant density, while niche generative AI skills temper competition.
Specialized generative AI and agentic skills are transferable across industries but still require domain-specific expertise.
Explicit years, mandatory generative AI experience, and specific technical stack requirements make filtering stringent.
Design, develop, and deploy production-grade AI applications leveraging Generative and Agentic AI frameworks.
Build scalable AI workflows using LLMs, multi-agent coordination, prompt engineering, and retrieval-augmented generation pipelines.
Ensure reliability, optimize performance, and contribute to AI engineering best practices and governance in collaboration with cross-functional teams.
2-4 years of professional software development experience (Dotnet/React/Full-stack).
Minimum 2 years hands-on experience building applications using Generative AI or agentic AI systems.
Strong proficiency in Python and backend engineering; experience designing RESTful APIs and scalable architectures.
Practical experience with LLM APIs, embeddings, vector search, or RAG pipelines; familiarity with autonomous agent frameworks.
Experienced engineer comfortable balancing experimentation with disciplined production engineering of AI-driven products.
Skilled in integrating advanced AI capabilities into real-world applications with an emphasis on scalability, reliability, and governance.
Able to lead AI best practices adoption and collaborate effectively with product managers, data teams, and software engineers.