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Job Description
Structured overview of role & requirementsAbout This Role
Lead development and deployment of LLM-powered AI agents and Generative AI systems impacting millions of users across sales, messaging, scheduling, and operations.
Build and fine-tune foundational models, retrieval-augmented generation (RAG) systems, and dynamic agents tailored to unique customer data and use cases.
Design, monitor, and iterate AI agent performance including prompt engineering and model evaluation, while collaborating cross-functionally and mentoring peers.
Minimum Requirements
8+ years experience in Data Science, Machine Learning, or Applied AI with production-grade model delivery.
Hands-on expertise with LLMs including fine-tuning, prompt engineering, function-calling agents, embeddings, and evaluation.
Experience building retrieval-augmented generation systems using vector DBs (e.g., FAISS, Pinecone, Weaviate) and deploying models in cloud-native environments (GCP, AWS).
Proficiency in Python with strong engineering practices; familiarity with frameworks like PyTorch, Transformers, MLOps, and agent orchestration tools like LangChain.
Ideal Candidate Profile
Technically strong individual contributor with proven track record taking AI/ML projects from research to scalable production.
Experienced in applied AI at intersection of agent design, core data science (causal inference, A/B testing, time-series forecasting), and GenAI.
Comfortable leading initiatives independently and collaboratively in a fast-paced environment while mentoring engineers and shaping AI technical standards.