The RoleWe're seeking a Sr. AI Software Engineer with deep expertise in building scalable AI platforms and developer tools. This role is ideal for someone passionate about enabling AI innovation through robust infrastructure, intuitive tooling, and seamless integration of cutting-edge models. You'll be at the forefront of operationalizing AI-designing systems that empower teams to build, deploy, and iterate on intelligent applications with speed and reliability.
What You Will Do- Platform Architecture & Development: Design and implement scalable AI platforms using Python. Integrate MLOps tools for model versioning, deployment, monitoring, and lifecycle management.
- AI Tooling & LLM Capabilities: Build tools and abstractions to interface with large language models, including prompting frameworks, agentic workflows (e.g., with LangGraph), and LLM orchestration services.
- Data Engineering & ETL: Collaborate with data teams to build robust ETL pipelines, preprocess training data, and construct feature workflows that feed AI models at scale.
- Reliability & Monitoring: Implement model monitoring dashboards to ensure platform reliability and performance, and investigate production prompt results.
- Research & Innovation: Stay ahead of cutting-edge trends in Generative AI. Prototype AI scenarios that unlock new product or operational value.
- Testing, Documentation & Standards: Define rigorous unit, integration, and performance testing methodologies. Maintain comprehensive documentation and enforce best practices for ethical and secure AI usage.
What You Bring- Bachelor's or Master's in Computer Science, Engineering, or related field
- 4+ years of experience building production-grade AI/ML platforms or developer-centric AI tools
- Strong software engineering skills in Python (preferred) and familiarity with Java/Go and OOP/data structures
- Familiarity with LLM prompting design, agentic workflows (e.g. LangGraph)
- Experience building and deploying on cloud platforms (AWS, Google Cloud, Azure); familiar with Docker and Kubernetes
- Solid understanding of MLOps principles: CI/CD, model versioning, monitoring, metrics
- Exceptional communication and collaboration across engineering and product teams
Nice to Have
- Experience with large-scale data pipelines (e.g., Apache Spark, Kafka)
- Certifications in cloud platforms, ML engineering, or specific AI tooling
- Awareness of AI ethics, biases, fairness, and data privacy protocols
We work together - literally. We're in-office 4 days a week in Palo Alto because the best ideas - and the fastest decisions - happen face to face. One day is yours to work wherever you're most effective.
The anticipated annual base salary range for this position is $150,000 - $250,000. Actual compensation may vary based on factors such as experience, skills, and location. This information is provided in accordance with the California Equal Pay Act.
