Senior Frontier Agents Engineer (Applied AI)

Навыки

Обязанности

• 01Design and deploy production AI agents leveraging the latest advances in large language models, reasoning, retrieval, memory, and tool use
• 02Architect intelligent systems that combine LLMs, traditional machine learning, structured knowledge, enterprise data, and deterministic software into reliable production workflows
• 03Engineer customer intelligence layers, retrieval pipelines, memory systems, and knowledge representations for reasoning over large, heterogeneous enterprise data
• 04Develop multi-agent systems that coordinate reasoning, planning, tool execution, and human oversight
• 05Translate frontier AI research into production systems by rapidly evaluating new models, prompting techniques, reasoning paradigms, and agent architectures
• 06Own the full experimentation lifecycle, from hypothesis generation to production rollout
• 07Design rigorous evaluation frameworks using offline benchmarks, online A/B experiments, golden datasets, regression suites, LLM-as-a-Judge, and human evaluation
• 08Run controlled experiments and ablation studies to understand the contribution of different models, prompts, retrieval strategies, reasoning techniques, memory systems, and agent architectures
• 09Continuously evaluate newly released frontier models
• 10Develop confidence estimation, reflection, and continuous learning systems that improve agents over time using real-world feedback
• 11Build production-quality AI systems with a strong emphasis on reliability, observability, latency, safety, and cost
• 12Design agent guardrails, fallback strategies, tracing, monitoring, and evaluation pipelines for safe deployment in high-stakes environments
• 13Collaborate with infrastructure engineers to deploy AI systems securely within enterprise cloud environments
• 14Build human-in-the-loop workflows that effectively combine AI automation with expert oversight
• 15Partner directly with enterprise customers to understand their business, data, and operational challenges
• 16Translate ambiguous customer problems into production AI architectures
• 17Rapidly prototype new ideas, validate them with customers, and evolve successful solutions into scalable production systems
• 18Identify reusable patterns that become core capabilities across many enterprise deployments

Требования

• 015+ years of software engineering, machine learning, or applied AI experience
• 02Strong Python programming skills
• 03Experience building production AI systems using LLMs
• 04Experience with modern AI tooling, including OpenAI, Claude, MCP, agent frameworks, vector databases, or retrieval systems
• 05Strong understanding of machine learning fundamentals and modern language models
• 06Experience designing or evaluating AI systems using quantitative metrics
• 07Excellent communication skills and the ability to work directly with enterprise customers