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 in-house 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, security, and compliance for AI features: prompt injection defenses, PII handling, abuse/hallucination controls, and audit trail.
- Contribute to internal AI tooling: SDKs, templates, and reusable components to accelerate future AI usecase.
