Lead AI Platform Engineer

Our client is undergoing a strategic shift toward AI-driven capabilities, with a focus on both customer-facing and employee-centric experiences. We are seeking a Lead AI Platform Engineer to establish and lead the firm’s internal AI engineering function, taking validated AI proof-of-concepts into secure, scalable production systems.

The organization currently partners with a vendor providing a customer-facing chat interface and agentic tooling, and has an internal performance analytics team focused on AI POCs. This role will serve as the technical owner of production AI, bridging experimentation and vendor solutions with enterprise-grade platforms built in AWS.

• Own the end-to-end productionization of AI solutions, transitioning proof-of-concepts from the performance analytics team into scalable, reliable production systems.
• Design, build, and operate the AI platform architecture supporting customer-facing and internal AI use cases.
• Serve as the internal technical counterpart to external AI vendors, integrating agentic workflows and tools into the enterprise environment.
• Establish AI engineering and MLOps standards, including CI/CD pipelines, model lifecycle management, monitoring, logging, and observability.
• Ensure AI systems meet enterprise requirements for security, scalability, reliability, and cost efficiency.
• Lead the design and implementation of observability frameworks for AI systems, including performance monitoring, error tracking, and model health.
• Build and scale an AI engineering team, setting technical direction, hiring strategy, and engineering best practices.
• Partner cross-functionally with product, analytics, infrastructure, and security teams to align AI initiatives with business priorities.
• Act as the technical face of AI engineering, helping position the team as the front line for AI innovation across the enterprise.

• 8+ years of experience in software, platform, or AI/ML engineering roles.
• Proven experience taking AI/ML proof-of-concepts into production within a large enterprise environment.
• Hands‑on experience designing and operating production‑grade AI platforms.
• Strong experience working in AWS‑based environments.
• Deep understanding of MLOps practices, including deployment, monitoring, versioning, and operational support.
• Experience integrating internally built systems with third‑party AI vendors or platforms.
• Strong backend engineering skills (Python required; additional languages a plus).
• Demonstrated ability to lead technically and build teams from the ground up.

• Experience supporting agentic AI or LLM‑based systems in production.
• Familiarity with customer-facing AI systems and internal enterprise tooling.
• Experience operating in complex or regulated enterprise environments.
• Prior experience standing up new engineering functions or centers of excellence.