Senior AI Engineer

A high-growth and reputable startup is rebuilding an entire industry's approach to data from the ground up, using AI agents to convert messy, unstructured information into clean, actionable intelligence at scale. Instead of bolting AI onto legacy systems, they built their platform natively around modern ML/AI, and it's already producing measurable results for enterprise customers across manufacturing, retail, and logistics. They've recently been recognized as one of the standout early-stage vendors in their space for momentum and technical innovation.

They're hiring a Senior AI Engineer to join the core engineering team and own the systems powering the AI platform. This is a backend and AI-first role built for someone who has actually shipped distributed, event-driven systems in production, and who has real, hands-on experience deploying and scaling LLMs and agents in live environments, not just spun up a demo. You'll work across a modern polyglot stack, partnering closely with the product engineering team to take new agent capabilities from prototype to production, while living in the AI systems powering the core product.

*** Candidates for this role must be currently living in the NYC metro area. ***

What You'll Do

• Deploy, optimize, and scale LLMs and AI agents in production, turning messy data into structured, usable intelligence
• Build and own the infrastructure layer supporting multi-agent orchestration across the platform
• Design, build, and scale backend services and distributed systems for high-throughput, real-time workloads
• Own reliability, observability, and performance across core backend services
• Partner with AI/ML and product teams to bring new capabilities from prototype to production

What You Need

• Experience working at an early-stage or growth-stage startup (must have)
• 6+ years backend engineering experience, Senior or Staff level impact
• 1+ year professional experience with LLMs, AI agents, or ML systems in production
• Deep expertise in distributed systems and event-driven architecture
• Hands-on AWS experience (ECS, Lambda, SQS, S3, etc.)
• Strong communication skills and a bias toward ownership