AI Engineer (production / apps focus):

Design and ship AI-powered product features (LLMs, RAG, agents, ML APIs) into our

existing services, working closely with backend, frontend, and data science teams.

 Integrate off-the-shelf and inhouse models (LLMs, embeddings, ML APIs) into robust

microservices and user facing flows.

 Design and implement RAG and workflow/agent pipelines: retrieval, context

assembly, tools integration, guardrails, and fallbacks.

 Own AI service reliability in production: latency, throughput, cost,

observability, circuitbreakers, and rollback/versioning of models and prompts.

 Collaborate with Data Scientists who own model training/finetuning and evaluation

design; productionize their outputs as stable APIs/workflows.

 Implement logging, feedback capture, and lightweight online evaluation hooks to

measure quality of AI features over time.

 Ensure safety, ...