Senior AI Engineer (Generative AI)

career; Pottersville (NY); Remote; USD 120,000 - 180,000; Full time

Job summary

A leading company is seeking a Senior AI Engineer to design and develop advanced AI systems utilizing Large Language Models and Generative AI technologies. The role requires extensive experience in machine learning, full-stack development, and a commitment to innovative, user-focused solutions. Candidates will lead development efforts from prototyping to production, alongside a small but dedicated team, in a rapidly evolving field aimed at transforming productivity.

Qualifications

• 4+ years in ML or AI engineering roles, focusing on NLP or GenAI.
• Deep understanding of modern LLMs and their application.
• Experience in full-stack development with Python and TypeScript.

Responsibilities

• Architect and implement scalable AI systems powered by LLMs.
• Lead end-to-end development including model integration.
• Monitor AI/ML performance and drive continuous improvement.

Skills

Machine Learning

Full-stack Development

Generative AI

NLP

Git/GitHub

Agile Methodologies

Tools

LangChain

Hugging Face

PostgreSQL

Docker

Job description

Who we are:

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

We're building IrisGo — your AI butler for the AI PC era. It understands how you work, observes your context, and automates what you shouldn’t have to do. We’re a small team of engineers and builders driven to solve hard problems — from browser automation to computer use, from local LLMs to full workflow orchestration. We believe the future of productivity is ambient, intuitive, and immersive. Our goal: reclaim your time and focus, one automated task at a time.

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.

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