Agent Harness Engineer - Backend + AI Systems Engineering

About This Role

Building the infrastructure that powers the next generation of AI is the core purpose of this engineering role. You will design the Agent Harness, which is the execution engine that enables AI agents to operate safely, efficiently, and at scale. This role involves building the core infrastructure behind enterprise AI systems used by over 200 companies and empowering over 120 in-house engineers with the SDKs, orchestration, and tooling they rely on every day.

Responsibilities

• Design and develop the execution layer that sits between large language models and enterprise applications
• Build LLM-centric execution engines and orchestration systems
• Design Agent SDKs used across the engineering organization
• Develop guardrails and policy engines for safe AI execution
• Implement model routing, context management, and memory architectures
• Optimize inference pipelines for performance, scalability, and cost
• Collaborate with AI researchers to bring cutting-edge research into production

Requirements

• Bachelor's degree (or equivalent practical experience) in Computer Science, Software Engineering, AI, Machine Learning, Mathematics, Physics, or a related field
• 5+ years of backend engineering experience
• Production development experience with Python
• Experience building production systems using LLMs or AI agents
• Strong experience designing and implementing distributed systems
• Experience developing RESTful APIs and/or gRPC services
• Business-level English communication skills

Nice to have:

• Experience with agent frameworks such as LangChain, LangGraph, AutoGen, or similar
• Cloud platform experience (AWS, GCP, or Azure)
• Knowledge of RAG, vector databases, and AI memory architectures
• Model routing and inference optimization
• Foundation software development in Go
• Kubernetes and container orchestration
• Event-driven architectures (Kafka, RabbitMQ, Pub/Sub)
• AI safety guardrails, policy execution, and observability
• ML infrastructure and MLOps experience

Benefits

• Build an in-house Agent Harness instead of relying on open-source frameworks
• Work at the intersection of AI/ML, distributed systems, and backend engineering
• Design SDKs and developer tools used by 120+ engineers
• Influence the architecture behind AI products serving 200+ enterprise customers
• Collaborate closely with Research Engineers to bring the latest AI innovations into production
• Enjoy significant technical ownership in a rapidly growing AI company