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Niche generative-AI specialization and non-metro, smaller-brand role reduces applicant density.
Strong generative-AI, deep learning, and vector-database requirements limit transferability across generalist roles.
Explicit 5–10 years requirement plus specialized generative-AI tooling and deployment mandates increases filtering strictness.
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Lead and manage end-to-end AI model lifecycle including data extraction, cleaning, pre-processing, training, and production deployment.
Develop scalable AI solutions using frameworks like Langchain and integrate vector databases (Azure Cognitive Search, Weavite, Pinecone).
Collaborate with cross-functional teams to define problem statements, prototype generative AI solutions, and ensure AI system robustness and scalability.
Bachelor’s or Master’s degree in computer science, data science, mathematics, or related field.
5-10 years of experience building Generative AI applications.
Proficiency in Python and deep learning frameworks such as TensorFlow, PyTorch, or Keras.
Experience with AI deployment and handling data quality processes including cleaning and validation strategies.
Experienced leader capable of managing a team of Gen-AI engineers and overseeing AI project lifecycles from data acquisition to model deployment.
Strong domain expertise in generative AI, statistical machine learning, NLP, and production-grade AI application development.
Technical familiarity with Langchain framework, vector databases, big data platforms (Apache Hadoop, Spark, Kafka, Hive), and Linux-based deployment environments.