Must Have Technical/Functional Skills
Python (PyTorch/TensorFlow) SQL API design; familiarity with LangChain/LlamaIndex Azure/AWS AI
GitHub Docker Kubernetes
Roles & Responsibilities
Define end-to-end AI/ML and GenAI architectures (data ingestion feature store model training inference monitoring).
Design LLM-based solutions: RAG pipelines prompt orchestration guardrails policy enforcement and human-in-the-loop workflows.
Select appropriate models (open source vs. hosted foundation models) vector databases embedding strategies and retrieval frameworks.
Author architecture artifacts: context diagrams sequence diagrams deployment topology decision records security controls and data lineage.
Lead data architecture for AI workload data quality labeling metadata PII handling and de-identification.
Establish MLOps: CI/CD for models feature store model registry automated evaluation canary rollout A/B testing drift monitoring.
Optimize cost and performance for training/inference (GPU/TPU selection quantization distillation batching).
Ensure data privacy consent and secure access (role-based control encryption KMS secret management).