Senior Lead - AI Engineering

ZS • Bellevue, WA

2d • Hybrid

About The Position

We are seeking a highly motivated Applied AI Engineer with a strong foundation in Machine Learning and a deep interest in Large Language Models (LLMs) and Generative AI. This role focuses on building, optimizing, and evaluating production-grade LLM systems, including Retrieval-Augmented Generation (RAG), fine-tuning workflows, and scalable inference pipelines.

Requirements

• A master's or bachelor's degree in Computer Science or related field from a top university
• 4+ years' hands-on experience in Machine Learning (ML) with production LLM systems
• Good fundamentals of machine learning, deep learning and fine tuning models (LLM) including: Understanding of transformer architectures, Prompt engineering expertise, Embeddings and vector search
• Experienced in backend API design with FastAPI, async patterns, rate limiting
• Experience with vector DB including: Pinecone, Weaviate, or Chroma, Embedding storage and similarity search, Hybrid search implementations
• Strong programming expertise in Python is must including: Async programming (asyncio, async/await), Type hints and Pydantic, SOLID principles and design patterns
• Experience in ML Ops to measure and track model performance including: MLFlow for model tracking, Langfuse for LLM observability (strongly preferred), Model versioning and A/B testing
• Experience in working with NLP & computer vision
• Fluency in English
• Client-first mentality
• Intense work ethic
• Collaborative spirit and problem-solving approach

Nice To Haves

• Langfuse for LLM observability

Responsibilities

• Design and implement LLM-powered applications using state-of-the-art transformer models.
• Build and optimize RAG pipelines using embeddings, chunking strategies, and vector search.
• Experiment with prompt engineering, structured outputs (JSON schemas/function calling), and tool-augmented LLMs (agents/workflows).
• Fine-tune models using techniques such as LoRA, PEFT, and instruction tuning.
• Develop and evaluate embedding models for similarity search and semantic retrieval.
• Conduct LLM evaluation using automated and human-in-the-loop techniques (offline + online).
• Optimize inference workflows for latency, GPU utilization, and cost efficiency (quantization, batching, caching).
• Build and maintain REST API Services (FastAPI etc.) to deploy LLM/RAG endpoints, integrate with product systems, and support scalable inference.
• Contribute to integration of AI systems into production software environments (CI/CD, monitoring, reliability).
• Research and prototype cutting-edge approaches in Generative AI and share learnings with the team.

Benefits

• Comprehensive total rewards package that supports your health and well‑being, financial future, time away, and professional development.
• Robust skills‑building programs
• Multiple career progression paths
• Internal mobility
• Deeply collaborative culture

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Associate degree