Senior Enterprise AI Engineer: Agentic Systems Lead

ozmocareers; United States; Remote; USD 180,000 - 210,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

401k matching

Paid time off

Remote work

Pawternity leave

Job summary

Ozmo is building agentic AI for enterprise SaaS and seeks a Senior Applied AI Engineer to own end-to-end production systems.

You will design agent architectures with LangGraph and LangChain, implement MCP servers and knowledge layers, ensure security and observability, and drive cost-aware tradeoffs. This fully remote role is open to candidates in the United States and offers a clear path from discovery to production.

Qualifications

• 7+ years of software engineering experience with production SaaS
• 2+ years of hands-on production LLM/agent experience
• Experience shipping AI products from prototype to production in customer-facing environments
• Hands-on experience with AI coding agents in daily development

Responsibilities

• Build and ship production-grade agentic AI products solving enterprise problems
• Own the full product lifecycle from discovery to GA and iteration
• Design agentic architectures with LangGraph, LangChain, CrewAI, or equivalent
• Develop MCP servers/tools, skills, and agent gateways
• Build knowledge retrieval layers with RAG and vector/graph databases
• Ensure security, multi-tenancy, auditability, and guardrails
• Establish observability and evaluation to monitor performance and cost
• Balance agent vs deterministic software decisions for quality and latency
• Own production systems end-to-end including deployment and incidents
• Create reusable patterns and mentor other engineers

Skills

LLM/Agent experience

Python

Distributed systems

Kubernetes

Cloud platforms (AWS/Azure/GCP)

API design

Tools

Claude Code

Codex

Cursor

Gemini CLI

Job description

Ozmo is building agentic AI for enterprise SaaS and seeks a Senior Applied AI Engineer to own end-to-end production systems.

You will design agent architectures with LangGraph and LangChain, implement MCP servers and knowledge layers, ensure security and observability, and drive cost-aware tradeoffs. This fully remote role is open to candidates in the United States and offers a clear path from discovery to production.