
Staff AI Engineer
2 weeks ago
Staff AI Engineer who will play a critical leadership role in shaping the architecture and delivery of AI-powered systems across the organization. You'll operate at the intersection of backend engineering and applied machine learning—designing resilient infrastructure, deploying cutting-edge models, and mentoring engineers across teams. This role goes beyond building software: it's about setting strategy, elevating engineering standards, and turning AI innovation into scalable, real-world impact.
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.
- 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.
- 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+ years 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 or GCP), and scalable API design
- Strong experience with MLOps tooling (e.g., Docker, Kubernetes, Airflow, MLflow) and model deployment practices
- Bachelor's or Master's degree in Computer Science, Engineering, or a related technical field
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