AI Engineer
Job in
San Jose, Santa Clara County, California, 95199, USA
Listed on 2026-06-19
Listing for:
University of Denver
Full Time
position Listed on 2026-06-19
Job specializations:
-
Software Development
AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Job Description & How to Apply Below
and the job listing Expires on July 17, 2026
San Jose, CA Experienced Alumni Jobs, Full-Time Job, Mid Career Alumni Jobs
We are seeking a motivated and innovative AI Engineer to contribute to the design, development, and deployment of scalable AI/ML solutions that power intelligent automation products and enterprise use cases.
This role is well-suited for individuals with a strong academic foundation and hands‑on exposure through projects or internships in AI/ML, data engineering, and cloud‑native AI deployment.
You will collaborate with cross‑functional teams including product managers, software engineers, architects, and data scientists to help build next‑generation AI capabilities.
Key Responsibilities- Design, develop, and optimize AI/ML models for enterprise applications.
- Build and deploy Generative AI and LLM‑powered solutions using modern AI frameworks.
- Develop scalable AI pipelines for training, inference, monitoring, and evaluation.
- Work with structured and unstructured data to create intelligent automation workflows.
- Fine‑tune open‑source and commercial LLMs for domain‑specific use cases.
- Integrate AI services into enterprise products using APIs and microservices.
- Collaborate with product and engineering teams to translate business requirements into AI solutions.
- Ensure model performance, scalability, security, and responsible AI practices.
- Conduct experiments, model benchmarking, and performance optimization.
- Stay updated with emerging AI technologies and industry trends.
Skills & Qualifications
- Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or related field.
- Strong proficiency in Python and AI/ML libraries such as Tensor Flow, PyTorch, Scikit‑learn, or Hugging Face.
- Hands‑on experience through academic projects, internships, or research in Generative AI, LLMs, RAG architectures, vector databases, and prompt engineering.
- Exposure to cloud platforms such as AWS, Azure, or GCP.
- Understanding of MLOps concepts and deployment tools (Docker, Kubernetes, MLflow, CI/CD pipelines).
- Familiarity with REST APIs, microservices, and distributed systems.
- Strong understanding of data structures, algorithms, and software engineering best practices.
- Strong understanding of full stack development using Python (FastAPI) and Next.js.
- Excellent problem‑solving and communication skills.
- Experience through academic, internship, or project work on enterprise AI solutions or intelligent automation platforms.
- Knowledge of NLP, reinforcement learning, or conversational AI.
- Exposure to Lang Chain, Llama Index, Pinecone, Weaviate, or similar AI ecosystems.
- Experience working in Agile development environments.
- Understanding of Responsible AI, AI governance, and model observability.
- Opportunity to work on cutting‑edge AI and automation technologies.
- Collaborative and innovation‑driven work environment.
- Competitive compensation and benefits.
- Learning and growth opportunities in AI, cloud, and enterprise platforms.
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