Back
Strong employer and metro location but niche agentic-GenAI skill reduces applicant density.
Highly specialized GenAI and agentic AI expertise limits transferability outside ML/AI roles.
Explicit 4-year requirement plus mandatory GenAI, agentic frameworks, cloud and production deployment skills make shortlisting strict.
Login to See Your Match Score
Create a free account or log in to unlock your CV match score across:
Develop, implement, and deploy agentic AI systems and solutions for complex enterprise use cases using various frameworks (LangGraph, CrewAI, Autogen) and cloud-native services (Azure AI Foundry, AWS Bedrock, GCP Vertex AI).
Design and optimize Retrieval-Augmented Generation (RAG) pipelines and prompt engineering strategies to enhance LLM-powered applications and workflows.
Collaborate cross-functionally to translate business requirements into technical implementations while monitoring solution performance and communicating progress to stakeholders.
Bachelor's and Master's degrees required.
Minimum 4 years of relevant work experience.
Proficiency in oral and written English.
Experience with AI development frameworks and cloud platforms (specific experience in Agentic AI and RAG architectures is expected).
Experienced in building production-grade Agentic AI solutions leveraging frameworks such as LangChain, LangGraph, CrewAI, or AutoGen.
Strong understanding of AI interoperability protocols and advanced RAG architectures.
Proficient in traditional AI/ML techniques including model building, fine-tuning, and evaluation, with practical knowledge of Responsible AI principles and cloud environments (AWS, Azure, or GCP).