Senior AI Engineer

Role Overview

We are seeking a Senior AI Engineer (5–7 years experience) to drive system architecture and execution within our lean AI engineering pods. You will build resilient, scalable backend infrastructure and construct complex agent topologies. You are expected to operate with high independence, lead technical design discussions, and maintain rigorous engineering standards across the entire delivery lifecycle.

Key Responsibilities

• System Architecture: Design and develop high-throughput, fault-tolerant Python services utilizing FastAPI, containerization, and EKS/Kubernetes orchestration.
• Advanced Agentic Engineering: Architect complex agent loops, state persistence strategies, tool integration layers, and multi-agent interaction systems.
• Evals & Observability Infrastructure: Establish robust evaluation frameworks, ground-truth benchmark datasets, logging pipelines, and real-time observability stacks.
• Trade-Off Analysis: Evaluate framework implementations (LangGraph, LangChain, Strands, ADK vs. custom components), documenting technical decisions and performance trade-offs.
• Independent Execution: Drive product delivery in a 2-person pod model without relying on large support teams, taking ownership from RFC/design to production deployment. Required Qualifications & Experience
• Experience: 5–7 years in backend production engineering and systems development.
• Agentic AI Expertise: 2–3+ years of production experience shipping multi-tool agentic applications into production environments.
• Technical Mastery: Deep knowledge of Python, FastAPI, microservices architecture, Docker, AWS EKS/Kubernetes, and CI/CD pipelines.
• Hands-on Production Track Record: Ability to explain end-to-end architectures of real-world systems you personally built, deployed, and monitored in production.
• Domain Depth: Complete grasp of agent execution loops, state management, ground-truth evaluations, and system observability tools.