Frontier Agents Engineer (Applied AI)

Overview

Frontier Agent Engineer (Applied AI) to bridge cutting-edge AI research with production deployment, working with enterprise customers to design, evaluate, and deploy intelligent agent systems.

What you'll do

• Design and deploy production AI agents leveraging large language models, reasoning, retrieval, memory, and tool use.
• Architect reliable workflows combining LLMs, traditional machine learning, structured knowledge, enterprise data, and deterministic software.
• Develop multi-agent systems for reasoning, planning, tool execution, and human oversight.
• Own experimentation from hypothesis generation through production rollout using offline benchmarks and online A/B tests.
• Evaluate new frontier models and determine where they improve quality, latency, reliability, or cost.
• Implement production-grade reliability, observability, latency, safety, and cost guardrails and evaluation pipelines.
• Partner with enterprise customers to translate ambiguous problems into production AI architectures and prototype solutions.

What you'll need

• 4+ years of software engineering, machine learning, or applied AI experience.
• Strong Python programming skills.
• Experience building production AI systems using LLMs.
• Experience with modern AI tooling, including OpenAI, Claude, MCP, agent frameworks, vector databases, or retrieval systems.
• Strong understanding of machine learning fundamentals and modern language models.
• Experience designing or evaluating AI systems using quantitative metrics.
• Excellent communication skills and ability to work directly with enterprise customers.

Nice to have

• Applied AI experience building production AI agents or autonomous systems.
• Deep understanding of reasoning, retrieval, memory, planning, and tool use.
• Experience designing evaluation frameworks for LLMs and agentic systems.
• Experience with RAG, semantic search, knowledge graphs, customer intelligence systems, or structured knowledge representations.