Platform Engineer

• Design, build, and operate infrastructure that supports the full AI lifecycle, including data ingestion pipelines, and fine‑tuning environments, inference services, prompt and agent execution, and orchestration layers
• Deploy and manage AI workloads using infrastructure‑as‑code, ensuring reproducible and auditable environments for development, testing, and production
• Automate provisioning of compute, storage, networking, and accelerators used by AI systems to minimize manual intervention and operational risk
• Operate and monitor AI platforms by measuring availability, latency, throughput, model performance, drift, and resource utilization
• Integrate AI services with internal and external systems
• Implement controls for secure model deployment, secrets management, access control, data handling, and encrypted communications across AI workflows
• Lead incident response and root‑cause analysis for AI service degradation, model failures, or infrastructure outages impacting production
• Plan and execute controlled deployments and upgrades of AI platforms, models, and orchestration components, including out‑of‑hours releases when required

• 2–3 years of experience in Platform Engineering, DevOps, or MLOps with direct responsibility for deploying and operating AI or data‑intensive systems
• Strong practical experience with Infrastructure as Code for AI environments (Terraform, CloudFormation, or equivalent)
• Experience operating cloud‑based AI platforms and services
• AWS experience is required
• Proficiency in scripting or programming languages used in AI platforms such as Python, Shell, Java, or similar
• Hands‑on experience building CI/CD pipelines for AI models, inference services, prompts, and agent workflows
• Strong understanding of networking and Linux administration as applied to high‑availability AI systems
• Experience with configuration management and automation tools used to manage AI infrastructure
• Security‑focused mindset with experience applying controls for model security, data protection, cryptography, and secrets management
• Ability to understand AI system behavior, business logic, and model constraints when operating production services
• Financial services or regulated‑industry experience is advantageous
• Availability for on‑call support to maintain uptime and reliability of production AI systems

Financial services or regulated‑industry experience is advantageous