AI Engineer (US)

EdgeQ Technologies•San Francisco, CA

4d•$100,000 - $180,000

About The Position

We are seeking a talented and motivated AI Engineer to design, develop, and deploy AI-powered applications using Python, large language models (LLMs), Retrieval-Augmented Generation (RAG), APIs, and deep learning frameworks such as PyTorch. The role involves building intelligent applications, integrating AI models into production systems, optimizing model performance, and developing scalable AI solutions to solve real-world business problems. The AI Engineer will work with software engineers, data scientists, product managers, and cross-functional teams. The position is full-time and may be based in San Francisco, California; New York City, New York; Seattle, Washington; or Austin, Texas. The annual salary range is $100,000–$180,000, depending on experience, skills, location, and qualifications. The employer offers a competitive compensation and benefits package subject to employer policy, opportunities to work on innovative AI and generative AI projects, professional development and career growth opportunities, and a collaborative, technology-driven work environment.

Requirements

1–5 years of experience in AI engineering, machine learning, software development, or a related field.
Strong programming skills in Python.
Hands-on knowledge of large language models (LLMs) and prompt engineering.
Experience developing RAG pipelines and LLM-powered applications.
Familiarity with PyTorch, machine learning fundamentals, and model evaluation.
Experience building and consuming REST APIs and integrating external AI services.
Knowledge of embeddings, vector search, and semantic retrieval.
Familiarity with Git, Docker, and modern software development practices.
Strong analytical, problem-solving, and debugging skills.
Good communication and collaboration skills.

Nice To Haves

Experience with LangChain, LlamaIndex, or similar LLM application frameworks.
Knowledge of vector databases such as Pinecone, Weaviate, Chroma, or FAISS.
Familiarity with cloud platforms such as AWS, Azure, or Google Cloud.
Experience with FastAPI, Flask, or other Python backend frameworks.
Understanding of fine-tuning, inference optimization, and model deployment.
Familiarity with AI agents, evaluation frameworks, and LLM observability.
Experience deploying scalable, production-ready AI applications.

Responsibilities

Design, develop, and deploy AI-powered applications using Python and modern AI technologies.
Build and optimize LLM-based applications using OpenAI, Hugging Face, or similar platforms.
Implement RAG pipelines for document retrieval and contextual question answering.
Develop AI agents, chatbots, virtual assistants, and intelligent automation solutions.
Integrate AI models with REST APIs, backend services, and third-party applications.
Work with vector databases and embedding models for semantic search and knowledge retrieval.
Use PyTorch and related machine learning frameworks to develop and evaluate AI models.
Optimize AI application performance, latency, accuracy, and scalability.
Implement prompt engineering, model evaluation, and responsible AI practices.
Collaborate with software engineers, data scientists, product managers, and cross-functional teams.
Write clean, maintainable, well-documented code and participate in code reviews.
Monitor deployed AI systems and troubleshoot technical issues.