Job Description
We are looking for a visionary Senior Generative AI Architect to spearhead the next evolution of our artificial intelligence infrastructure. As we prepare for the technological landscape of 2026, we need a leader who can bridge the gap between cutting-edge research and scalable production systems.
In this pivotal role, you will design and deploy large-scale generative models, optimize inference pipelines, and define the architectural standards for our AI-driven products. You will work closely with cross-functional teams to integrate LLMs, Vector Databases, and MLOps best practices into our core stack.
Why Join Us?
• Work on high-impact projects that shape the future of enterprise AI.
• Competitive compensation and equity package.
• Flexible remote-first policy with premium San Francisco amenities.
Responsibilities
- Architectural Leadership: Design and oversee the implementation of robust, scalable Generative AI architectures using LLMs and RAG frameworks.
- Pipeline Optimization: Build and maintain high-throughput, low-latency inference pipelines to ensure optimal model performance in production environments.
- Research & Innovation: Stay at the forefront of AI trends, evaluating new models (e.g., GPT-4, Claude, Llama 3) and integrating them into our ecosystem.
- MLOps Integration: Implement CI/CD pipelines for machine learning, utilizing tools like Kubernetes, Docker, and Airflow.
- Collaboration: Partner with data scientists, software engineers, and product managers to translate business requirements into technical AI solutions.
- Model Evaluation: Establish rigorous testing and evaluation frameworks to ensure model safety, accuracy, and alignment with business goals.
Qualifications
- Education: Master’s degree or PhD in Computer Science, Machine Learning, Mathematics, or a related quantitative field.
- Experience: 5+ years of professional experience in software engineering, with at least 3 years specifically focused on AI/ML or Generative AI.
- Technical Skills: Proficiency in Python, PyTorch, or TensorFlow; deep understanding of Transformer architectures and NLP.
- Infrastructure: Experience with cloud platforms (AWS/GCP/Azure) and vector databases (Pinecone, Milvus, Weaviate).
- Problem Solving: Proven ability to solve complex technical problems and improve system reliability.
- Communication: Excellent verbal and written communication skills with the ability to explain complex technical concepts to non-technical stakeholders.