Senior AI Engineer (Generative AI)

AI Fund; United States; On-site; USD 100,000 - 720,000; Full time

Job summary

Join a leading company as a Senior AI Engineer where you'll develop cutting-edge AI systems utilizing Large Language Models. This role requires a strong blend of engineering and product focus, with responsibilities from development to deployment, all while driving the future of human-computer interaction.

Benefits

Flexible working hours

Professional development opportunities

Health benefits

Qualifications

• 4+ years in ML or AI engineering roles with focus on NLP or GenAI.
• Hands-on experience implementing GenAI techniques.
• Solid foundation in full-stack development.

Responsibilities

• Architect and implement scalable AI systems powered by LLMs.
• Lead end-to-end development efforts for AI applications.
• Monitor AI/ML performance in production and drive improvements.

Skills

Machine Learning

Generative AI

NLP

Full-stack development

Agile methodology

Collaboration

Tools

LangChain

Hugging Face

PostgreSQL

Docker

Job description

Join to apply for the Senior AI Engineer (Generative AI) role at AI Fund

Join to apply for the Senior AI Engineer (Generative AI) role at AI Fund

AI workflow is broken. Digital work is buried under copy-paste routines, fragmented tools, and repetitive tasks that drain our time and focus.

Based in California and Taipei, we bring deep roots in full-stack engineering, machine learning, and product design. If you want to build the future of human-computer interaction, we’re hiring.

About the Role

We’re seeking a Senior AI Engineer with extensive hands-on experience developing products powered by Large Language Models (LLMs) and Generative AI technologies. This role is ideal for an engineer who brings a depth of experience in machine learning, a strong full-stack background, and a product-driven mindset.

You’ll help lead the design and development of advanced AI systems—from building prototypes to scaling production systems. The ideal candidate is excited by the challenge of applying cutting-edge AI in meaningful, user-focused ways, and thrives at the intersection of R&D, engineering, and product.

What You’ll Do:

• Architect and implement scalable AI systems and applications powered by LLMs and multi-agent frameworks.
• Lead end-to-end development efforts, including model integration, infrastructure design, and application logic.
• Prototype and deploy GenAI applications that combine retrieval, tool use, reasoning, and interactivity.
• Contribute to decision-making around model selection, finetuning, evaluation, and safety mechanisms.
• Monitor AI/ML performance in production and drive continuous improvement of prompt, RAG, and agent pipelines.
• Stay at the forefront of GenAI developments and bring innovative ideas into the product roadmap.

What You Must Bring:

• 4+ years of experience working in ML or AI engineering roles, ideally with a focus on NLP or GenAI.
• Deep understanding of how modern LLMs work, including transformer architectures, finetuning, and evaluation.
• Hands-on experience implementing and optimizing GenAI techniques such as: Tool/function calling, Multi-agent workflows, Retrieval-Augmented Generation (RAG), Finetuning or custom training (e.g., LoRA, PEFT), and Structured prompting and evaluation.
• Proficiency with GenAI frameworks and tools (e.g., LangChain, LlamaIndex, Hugging Face, Haystack).
• Experience integrating LLMs into real-world applications, including building internal tooling or customer-facing AI features.
• Solid foundation in full-stack development or backend systems (Python, TypeScript, FastAPI, etc.).
• Experience designing and deploying scalable APIs and cloud infrastructure (AWS, GCP, or Azure).
• Proficient with databases (PostgreSQL, MongoDB, or vector DBs like Pinecone or Weaviate).
• Comfortable working in agile product teams and balancing experimentation with shipping reliable code.
• Strong Git/GitHub collaboration skills and comfort working with CI/CD workflows and containerization (Docker, etc.).

Bonus Points:

• Experience working in a startup or research-oriented environment.
• Prior exposure to open-source AI models (e.g., LLaMA, Mistral, Mixtral) and fine-tuning them.
• Publications, technical blog posts, or demos of past AI work.

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Contract

Job function

• Industries

  Software Development

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