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Remote, mid-senior GenAI lead with broad LLM and cloud requirements increases applicant competition.
Specialized GenAI/Agentic LLM expertise makes industry transitions harder despite transferable ML foundations.
Explicit 5–10 years plus mandatory GenAI, LLMOps, Snowflake, and fine-tuning expertise increases strictness.
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Design and implement end-to-end enterprise-grade Generative AI and Agentic AI solutions including data pipelines, model selection, prompt engineering, evaluation, and deployment.
Define success criteria, evaluation plans, and acceptance thresholds ensuring solutions are effective, safe, and production-ready with measurable impact.
Lead structured experimentation, failure diagnosis, and iterative improvement of AI models and prompting strategies while collaborating with cross-functional teams for integration and operations.
5-10 years of overall AI/ML experience with at least 2-3 years specifically in Generative AI solutions.
Strong expertise in LLMs, Azure AI, Snowflake, MLOps, LLMOps, prompt engineering, RAG design, and Agentic AI SDLC implementation.
Proficiency in Python and major ML frameworks like PyTorch, TensorFlow, Scikit-learn.
Work Experience Required: 5-10 years overall AI/ML experience; explicit notice period not mentioned.
Experienced in architecting and delivering production-ready AI/ML systems with strong client-facing and delivery accountability.
Skilled in rigorous evaluation design and data curation, with an evidence-based approach to model improvement and risk management.
Comfortable working in cloud-native AI environments (Azure, AWS, Snowflake) and collaborating closely with AI engineers, data engineers, product, and platform teams.