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Sr. Software Engineer, Applied AI

Job in Irvine, Orange County, California, 92713, USA
Listing for: Hyundai Autoever America
Full Time position
Listed on 2026-02-28
Job specializations:
  • Software Development
    AI Engineer, Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 80000 - 100000 USD Yearly USD 80000.00 100000.00 YEAR
Job Description & How to Apply Below
Position: 10850 – Sr. Software Engineer, Applied AI

Company Overview

Hyundai Auto Ever America (HAEA) is the dynamic IT powerhouse behind Hyundai Motor Corporation, a Fortune 500 global leader in the automotive industry. As a key affiliate, we provide cutting‑edge IT services and support to top brands including Kia, Genesis, Hyundai Translead, Hyundai Mobis, Hyundai Capital, and Glovis. HAEA offers a truly global and collaborative environment. Here, you’ll drive innovation, boost operational efficiency, and help shape the future of mobility for the Hyundai Motor Group.

At HAEA, we understand that IT is the cornerstone of today’s fast‑evolving digital world. By uniting all IT resources under one roof, we deliver consistent, top‑quality solutions while serving as the crucial information link between Hyundai’s Global Headquarters and North American operations. If you’re passionate about technology and eager to make a real impact at a world‑class company, Hyundai Auto Ever America is the place to grow your career.

Join us and be part of the transformation that’s driving the future of automotive innovation.

Role Overview

Hyundai Auto Ever America 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.

What You Will Do
  • 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.
Basic Requirements
  • Bachelor’s or Master’s degree in computer science, Engineering or a related field; advanced degrees or industry certifications are a plus.
  • 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 Auto Gen, Lang Graph, Llama Index, CrewAI, and n8n, with strong knowledge of multi‑agent orchestration patterns.
  • Strong proficiency in Python and core AI/ML tooling, including Tensor Flow or PyTorch, the Hugging Face ecosystem, and common AI orchestration frameworks.
  • Deep experience with vector databases (Pinecone, Chroma

    DB, FAISS) and embedding‑based retrieval techniques.
  • Advanced understanding of prompt engineering, RAG architectures, model evaluation, and LLM optimization strategies.
  • Practical experience with cloud AI platforms such as AWS Sage Maker/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/No

    SQL databases, Docker, and Kubernetes.
  • Experience implementing the Model Context Protocol (MCP) to improve context sharing, interoperability, and coordination across multi‑agent systems.

Please note this job description is not designed to cover or contain a comprehensive listing of activities, duties or responsibilities that are required of the employee for this job. Duties, responsibilities, and activities may change at…

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