Staff AI Engineer

You will

• Own the architecture and implementation of distributed, high-scale backend systems and APIs that serve machine learning models in production.
• Lead technical design for AI integration across product lines, enabling real-time and batch inference workflows using LLMs, transformers, and classification models.
• Drive the fine-tuning and deployment of pre-trained models (e.g., from Hugging Face or OpenAI) for mission-critical business use cases in domains such as healthcare, finance, or operations.
• Integrate external AI services where appropriate and evaluate trade-offs for build vs. buy decisions.
• Define and evolve platform-wide standards for backend engineering, MLOps, model governance, and observability.
• Mentor and support senior and mid-level engineers, both within your team and across functions, to elevate system design and code quality.
• Collaborate with cross-functional leaders in product, ML research, data engineering, and DevOps to align technical initiatives with business goals.
• Influence AI strategy and roadmap, evaluating emerging technologies and frameworks for future adoption.
• Lead root-cause analyses and performance tuning to ensure systems remain reliable, efficient, and scalable.

You are

• A senior technical leader with a demonstrated ability to architect, build, and scale AI-backed systems in production environments.
• Comfortable operating across layers—from backend API services to AI Services and ML model lifecycle management—while driving architectural clarity and system-level thinking.
• Experienced in bridging the gap between research and production, with a strong focus on reliability, maintainability, and business outcomes.
• Skilled at leading cross-team initiatives, guiding technical direction, and fostering a high-trust engineering culture.
• Able to influence without authority, collaborating across teams to align on complex technical trade-offs.
• Deeply invested in engineering excellence, with a strong bias toward automation, observability, and security.

You have

• 8+ years of professional software engineering experience, including 2+ years at the Staff Engineer level or equivalent.
• 4+ years of experience with backend development in TypeScript, Node.js, and SQL-based RDBMS (e.g., PostgreSQL, MySQL).
• 1+ year deploying ML/AI models to production, with hands-on experience fine-tuning LLMs or transformer-based models.
• Deep understanding of system architecture, cloud infrastructure (AWS), and scalable API design.
• Strong experience with Data Pipeline tooling (e.g., Docker, Kubernetes, dbt, Dagster) and model deployment practices.
• Proven leadership in setting technical direction, mentoring engineers, and driving cross-team projects to completion.
• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related technical field.