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Niche Agentic/GenAI and Langchain skills reduce applicant density despite metro location.
Specialized Agentic/GenAI expertise moderately limits cross-industry transferability but core ML skills remain transferable.
Multiple mandatory GenAI, LLM, RAG, vector DB, and deployment skills enforce strict shortlisting.
Develop and deliver Agentic AI projects, including GenAI applications and RAG pipelines, ensuring quality and alignment with architecture.
Translate architectural designs into prototypes and production-ready services, optimizing existing Agentic AI models and workflows.
Manage end-to-end deployment and scaling of AI models using cloud services and enforce engineering best practices through code reviews.
Strong proficiency in Python for AI/ML engineering or software development.
Experience with GenAI, LLMs, Transformer models, and Agentic AI solutions.
Exposure to vector databases, RAG architectures, MCP, and Agent-to-Agent communication.
Familiarity with SQL/NoSQL databases and CI/CD tools like Docker and Kubernetes for AI model deployment.
Experienced in designing and optimizing scalable, production-grade Agentic AI workflows and models.
Capable of managing AI project lifecycle from data preprocessing to deployment in cloud environments (AWS, Azure, or GCP).
Skilled in integrating complex AI components including prompt engineering, APIs, and multiple data storage technologies.