Senior AI Ops / MLOps Engineer

we aren't building a single, generic chatbot. We are building a Composable AI Microservice Architecture, a swarm of hundreds of hyper-specialized AI services, each meticulously "programmed" to solve small, focused tasks with high precision. This fleet powers Ava, our AI support engine, and a suite of cutting-edge generative tools for travel and expense management.
As a Senior AI Ops / MLOps Engineer, you are the architect of the platform that makes this scale possible. You will move beyond traditional MLOps to manage a "factory" of Language Models. Your challenge is one of orchestration and standardization, ensuring that every service in the swarm meets a rigorous bar for quality, reliability, and cost-efficiency.
What You'll Do:
Orchestrate the AI Fleet: Build and own the runtime environment for 100+ specialized AI services. Manage model routing, context versioning, and standardized memory/history stores.
High-Density Inference Optimization: Design and implement SageMaker Multi-Model Endpoints (MME) and Inference Components to serve multiple tuned SLMs per GPU, maximizing hardware utilization while minimizing latency.
Deterministic Service Excellence: Treat reliability as a layered engineering problem. Build deterministic "shells" around probabilistic LM outputs, prioritizing data-layer validation and strict serialization.
Automated Evaluation & Observability: Implement "LLM-as-a-judge" patterns and automated benchmarking to detect semantic drift and hallucinations across the fleet before they impact the user.
Standardize the Workflow: Obsess over building reusable patterns and Terraform-based infrastructure that eliminate "snowflake" configurations, allowing us to deploy new specialized AI tasks in minutes.
Agency Strategy: Partner with AI Researchers to find the "Goldilocks zone" for agentic autonomy-balancing the flexibility of LLM tool-use with the precision required for production stability.