Staff AI Engineer – AI Platform

About This Opportunity

We are representing a confidential SaaS organization seeking a Staff AI Engineer to join their platform engineering team. Our client is building next-generation workplace software with AI at its core, and this role sits at the intersection of infrastructure and applied machine learning. You'll architect scalable AI platform services while directly applying LLMs to solve real user problems and drive product innovation.

Responsibilities

• Architect, design, and implement scalable AI platform services that support deployment, orchestration, and lifecycle management of LLMs and other AI models
• Apply LLMs and AI technologies directly to build and enhance intelligent product features, collaborating closely with product and engineering teams
• Build and maintain robust APIs and backend systems that enable seamless integration of AI-powered capabilities into the core platform
• Develop infrastructure for model serving, monitoring, logging, and automated evaluation to ensure high reliability and performance in production
• Integrate with multiple LLM providers (OpenAI, Anthropic, Google) and manage model selection, routing, and fallback strategies for optimal performance and cost
• Drive adoption of best practices in AI privacy, security, and compliance, including data anonymization, secure data handling, and regulatory adherence
• Optimize platform performance, scalability, and cost-efficiency using cloud-native technologies and distributed systems
• Stay current with advancements in AI infrastructure, MLOps, and LLM applications, proactively incorporating innovations into the platform
• Collaborate cross-functionally with product, frontend, and data teams to deliver seamless, user-centric AI experiences

What We're Looking For

• Extensive experience designing and building scalable AI/ML platforms or infrastructure in production environments
• Proven track record of applying LLMs and AI models to real-world product features and user-facing solutions
• Deep expertise in backend engineering, distributed systems, and cloud-native technologies (Kubernetes, Docker, AWS/GCP/Azure)
• Experience integrating and managing multiple LLMs and AI models, with strong understanding of their operational requirements and limitations
• Proficiency in orchestration frameworks and workflow engines (LangGraph, Airflow, Kubeflow, Ray, or similar)
• Strong programming skills in Python, Go, TypeScript, or similar languages for backend and AI platform development
• Experience with MLOps best practices, including model deployment, monitoring, logging, and automated evaluation
• Demonstrated ability to address AI privacy and security challenges, including data anonymization and compliance with data protection regulations
• Familiarity with search technologies and their integration into AI-driven applications
• Excellent collaboration and communication skills with a track record of effective cross-functional work
• Passion for staying at the forefront of AI infrastructure and applying new technologies to solve problems at scale

How We Work With You

When you apply through Get A Job.ai, our talent team will review your profile and schedule an initial screening call to understand your background and interests. If there's a strong match, we'll submit your candidacy to our client for consideration. Throughout the interview process, we'll provide guidance and support to help you put your best foot forward. Please do not contact the client directly—all communication should go through our recruiting team to ensure a smooth process.

Pay

Compensation details will be discussed during the screening process and are competitive with senior AI engineering roles at high-growth technology companies.

Equal Opportunity

Get A Job.ai is committed to equal employment opportunity. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or other protected characteristics.