Senior Applied AI Engineer

Ozmo

3d • $180,000 • Remote

About The Position

We are seeking a Senior Applied AI Engineer to build and ship production-grade agentic AI products that solve real, mission-critical enterprise problems. This role involves owning the full product lifecycle from discovery and prototyping through customer pilots, GA, and ongoing iteration. You will design agentic architectures using frameworks like LangGraph, LangChain, CrewAI, or PydanticAI, focusing on planning, decomposition, tool use, multi-step workflows, memory, state management, self-correction, and human-in-the-loop patterns. You will also build the agent infrastructure layer, including MCP servers/tools, skills, agent gateways, and agent-to-agent communication, as well as the knowledge and retrieval layer with RAG, hybrid graph/vector retrieval, taxonomy, ontology, metadata, provenance, and content lifecycle management. A key aspect of this role is designing for enterprise-grade security and trust, including authorization, tenant isolation, auditability, guardrails, prompt-injection protection, and controlled tool access. You will build rigorous evaluation and observability systems to measure task success, quality, latency, cost, drift, and reliability, and make sound architectural tradeoffs. You will own systems in production end-to-end, including deployment, monitoring, incident response, performance, reliability, and cost. Additionally, you will create reusable patterns and tooling, mentor other engineers, and help establish how Ozmo builds with AI.

Requirements

• 7+ years of software engineering experience, with substantial experience building and operating production SaaS.
• 2+ years of hands-on production LLM/agent experience, with demonstrated systems shipped to real users.
• Proven track record of taking AI products from prototype through pilot and into production, ideally in customer-facing environments.
• Practical experience using AI coding agents such as Claude Code, Codex, Cursor, Gemini CLI, or similar tools as part of your day-to-day development.
• Deep hands-on experience building agentic systems, including tool use, orchestration, planning, multi-agent workflows, and human-in-the-loop systems.
• Strong understanding of AI infrastructure, particularly MCP, agent gateways, skills, memory, evaluation, observability, and interoperability.
• Strong knowledge of RAG and knowledge systems, including hybrid retrieval, vector + graph databases, metadata, taxonomy/ontology, and retrieval evaluation.
• Strong enterprise engineering fundamentals, including multi-tenancy, security, authorization, auditability, reliability, and distributed systems.
• Production cloud-native experience, including Kubernetes, CI/CD, infrastructure-as-code, Docker, and AWS/Azure/GCP.
• Expert-level Python and strong software architecture skills, including API design, data modeling, testing, performance, and distributed systems.
• Exceptional technical judgment and communication, with the ability to explain non-deterministic AI behavior, make pragmatic tradeoffs, mentor engineers, and take ownership of outcomes.

Responsibilities

• Build and ship production-grade agentic AI products that solve real, mission-critical enterprise problems.
• Own the full product lifecycle from discovery and prototyping through customer pilots, GA, and ongoing iteration.
• Design agentic architectures with LangGraph, LangChain, CrewAI, PydanticAI, or equivalent: planning, decomposition, tool use, multi-step workflows, memory, state management, self-correction, and human-in-the-loop patterns.
• Build the agent infrastructure layer including MCP servers/tools, skills, agent gateways, and agent-to-agent communication.
• Build the knowledge and retrieval layer including RAG, hybrid graph/vector retrieval, taxonomy, ontology, metadata, provenance, and content lifecycle management.
• Design for enterprise-grade security and trust, including authorization, tenant isolation, auditability, guardrails, prompt-injection protection, and controlled tool access.
• Build rigorous evaluation and observability systems that measure task success, quality, latency, cost, drift, and reliability. Use them to catch regressions before release and monitor performance in production.
• Make sound architectural tradeoffs about when to use agents versus deterministic software, balancing accuracy, reliability, latency, complexity, and cost.
• Own systems in production end-to-end, including deployment, monitoring, incident response, performance, reliability, and cost.
• Create reusable patterns and tooling, mentor other engineers, and help establish how Ozmo builds with AI.

Benefits

• Medical, vision, dental and life insurance along with short- and long-term disability
• Plenty of paid time off (PTO) that grows the longer you’re with Ozmo, as well as paid holidays
• 401k to save for retirement with employer matching
• Paid maternity and bonding leave for new parents
• Paid pawternity leave when you bring a new pet into your life
• One-month sabbatical after you have been with Ozmo for five years
• Flexible, remote work arrangements to support your best work

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed