10850 – Sr. Software Engineer, Applied AI

Hyundai Autoever America•Irvine, CA

1d•$103,170 - $158,873

About The Position

Hyundai AutoEver America (HAEA) is seeking an innovative Sr. Software Engineer - Applied AI Engineer to design, build, and operationalize real‑world AI solutions that enhance automotive industry applications. This role focuses on developing LLM‑powered applications, RAG systems, intelligent agents, and full‑stack AI workflows—from prototype through production. You will translate business needs into scalable AI systems, integrate models into cloud environments, and collaborate across engineering, product, and data teams to deliver impactful, user‑centric AI capabilities. This is a hands‑on engineering role ideal for someone passionate about applying modern AI in practical, high‑value scenarios.

Requirements

Bachelor’s or master’s degree in computer science, engineering or a related field.
8+ years of software engineering experience, including 3+ years focused on AI/ML solution development.
Proven experience delivering production-ready AI systems, including LLM-based applications, traditional ML models, RAG pipelines, and agentic/automated workflows.
Hands-on expertise with modern agent frameworks such as AutoGen, LangGraph, LlamaIndex, CrewAI, and n8n, with strong knowledge of multi-agent orchestration patterns.
Strong proficiency in Python and core AI/ML tooling, including TensorFlow or PyTorch, the Hugging Face ecosystem, and common AI orchestration frameworks.
Deep experience with vector databases (Pinecone, ChromaDB, FAISS) and embedding-based retrieval techniques.
Advanced understanding of prompt engineering, RAG architecture, model evaluation, and LLM optimization strategies.
Practical experience with cloud AI platforms such as AWS SageMaker/Bedrock, Azure OpenAI, or Azure AI Foundry, along with ML Ops best practices (CI/CD, testing, model monitoring, observability).
Proficiency with full-stack and cloud-native development, including React, microservice APIs, relational/NoSQL databases, Docker, and Kubernetes.
Experience implementing the Model Context Protocol (MCP) to improve context sharing, interoperability, and coordination across multi-agent systems.

Responsibilities

Design and implement applied AI solutions, including LLM applications, RAG pipelines, agentic workflows, predictive models, and generative AI tools.
Develop full‑stack AI applications, building front‑end interfaces and integrating them with backend services and cloud architecture.
Build production‑ready AI systems that integrate with enterprise platforms, and user-facing automotive applications.
Own applied experimentation, prototype rapid PoCs/MVPs, refine prompts, iterate on model performance, and enhance AI reliability.
Collaborate with cross-functional teams to translate requirements into AI capabilities and ensure solutions meet governance, privacy, and security standards.