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Protocol Intelligence
Data-driven signals on your job's competitivenessMid-level AI/GenAI role with broad cloud and LLM requirements yields moderate competition.
Specialized GenAI, cloud data platform, and vector DB expertise reduces cross-industry transferability.
Explicit 6+ years and mandatory cloud, data engineering, and GenAI stack make candidate filtering strict.
Job Description
Structured overview of role & requirementsAbout This Role
Design, develop, and productionize AI and Generative AI capabilities integrated with an enterprise cloud data platform, focusing on LLM applications, RAG solutions, AI agents, and vector database technologies.
Enhance and extend scalable enterprise cloud data platform including data ingestion, transformation, processing pipelines, and reusable APIs to support AI applications.
Translate business requirements into scalable AI/data engineering solutions, conduct technical POCs, collaborate with cross-functional teams, and ensure integration with data architecture and security standards.
Minimum Requirements
6+ years of experience in Data Engineering / Cloud Data Platforms.
Minimum 1+ year hands-on experience in AI, Generative AI, LLM-based applications, or ML engineering.
Strong technical skills with Python, SQL, Apache Spark, REST APIs, and experience with cloud platforms (AWS, Azure, or GCP).
Bachelor's or Master's degree in Computer Science, Information Technology, Data Science, Artificial Intelligence, Engineering or related technical discipline.
Ideal Candidate Profile
Experienced in building enterprise-grade Generative AI applications beyond prototypes, especially implementing RAG over enterprise data sources.
Skilled in integrating AI applications with databases, APIs, enterprise apps, document repositories, and managing AI evaluation, monitoring, and responsible AI controls.
Familiar with cloud-native data technologies (Databricks, Snowflake, Delta Lake), AI orchestration frameworks (LangChain, LlamaIndex), and vector databases (Pinecone, Weaviate).