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Tier-1 brand and mid-level AI role attract many applicants despite niche generative AI requirements.
Applied GenAI and production ML skills transfer across industries but require specific AI tooling experience.
Explicit four-year requirement plus specialized GenAI, cloud, and production deployment skills elevate screening strictness.
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Develop and deploy agentic AI systems and solutions for complex enterprise use cases using frameworks like LangGraph, CrewAI, and cloud-native services (Azure AI Foundry, AWS Bedrock Agents, GCP Vertex AI Agent Builder).
Design, implement, and optimize retrieval-augmented generation (RAG) pipelines and prompt engineering strategies to improve LLM-powered applications and workflows.
Collaborate with cross-functional teams to translate business requirements into technical implementations, monitor solution performance, and communicate technical findings to stakeholders.
Bachelor's degree required.
Minimum 4 years of relevant work experience in data science or AI development.
Proficiency in English (oral and written).
Experience with production deployment of agentic AI solutions and use of cloud AI services (Azure, AWS, or GCP).
Experienced in building and deploying agentic AI solutions using LangChain, LangGraph, CrewAI, or AutoGen frameworks.
Strong knowledge of AI interoperability protocols (MCP, A2A) and advanced RAG architectures (Graph RAG, Vectorless RAG, Hybrid RAG).
Skilled in traditional AI/ML techniques including model building, fine-tuning, and evaluation, with familiarity in Responsible AI principles and security practices for GenAI deployments.