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Remote role and mid-tier brand increase applicant pool, but strong GenAI specialization moderates competition.
Highly domain-specific GenAI/NLP skills and production experience limit cross-industry transferability.
Many mandatory senior technical skills, production GenAI experience, and explicit 8+ years make filters highly strict.
Architect and implement scalable Generative AI and Agentic AI solutions end-to-end, ensuring enterprise-grade reliability and performance on Azure or AWS.
Translate client business and technical requirements into robust technical designs and high-level architectures focused on extensibility, scalability, security, and non-functional requirements.
Develop, productionize, and scale AI/ML pipelines and GenAI solutions including prompt engineering, RAG architectures, fine-tuning, and integration via APIs (FastAPI with ORM).
8+ years total experience in AI/ML with deep expertise in Large Language Models (LLMs) and Transformer architectures.
Proficient in Python programming with strong experience in AI/ML libraries (e.g., Hugging Face, LangChain, PyTorch, TensorFlow) and production-grade coding practices.
Experience deploying and scaling GenAI solutions in production on Azure or AWS cloud platforms.
Bachelor’s or master’s degree in Computer Science, Information Technology, or related field.
Deep hands-on expertise in prompt engineering, retrieval-augmented generation (RAG) patterns, and fine-tuning/distillation of LLMs in production environments.
Proven ability to architect end-to-end GenAI systems, including API design and integration, working with vector databases, and implementing NFR considerations.
Experienced in cross-functional collaboration to translate complex business needs into AI-driven technical solutions for enterprise-scale deployments.