Associate Manager, AI Engineering - Taco Bell Voice AI

Description

We are hiring an Associate Manager, AI Engineering to help design and improve voice-based AI agents for Taco Bell drive-thru operations. These roles are perfect for early-career AI engineers or data scientists looking to expand their skills in LLM-based interaction design, speech system optimization, and production-quality prompt development.

Key Responsibilities:

Prompt Engineering & Agent Design:

• Author and refine prompt instructions, chaining logic, and fallback strategies.
• Design and test multi-turn conversation flows aligned to Taco Bell brand voice.
• Build and maintain system personas and error handling routines.

Model Tuning & Evaluation:

• Fine-tune LLMs, ASR models, and embedding systems under supervision.
• Assist in running experiments using LoRA, distillation, or pruning methods.
• Contribute to agent evaluation metrics, regression tracking, and A/B tests.

Cross-Functional Collaboration:

• Work closely with MLEs on model integration and performance tuning.
• Partner with QA and PMs to improve agent usability, reliability, and task success rates.
• Help manage RAG components, context retrieval chains, and structured data inputs.

Required Qualifications:

• 1–3 years experience in AI Engineering, Data Science, or ML-related roles.
• Proficiency in Python and AI frameworks (e.g., LangChain, HuggingFace, OpenAI APIs).
• Understanding of prompt engineering, agent flows, and model evaluation principles.
• Interest in LLM tuning, ASR modeling, or speech interaction design.

Preferred Qualifications:

• Experience with RAG, vector search, embeddings, or retrieval-based models.
• Exposure to ASR systems or speech pipelines.
• Familiarity with LoRA, distillation, or low-latency AI architectures.

Location & Travel:

• This role is remote.
• Occasional travel to test markets or pilot sites may be required.

Salary Range: $134,500-$148,300 annually + bonus eligibility. This is the expected salary range for this position. Ultimately, in determining pay, we'll consider the successful candidate’s location, experience, and other job-related factors.