AI Engineer

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Company Overview

A leading AI infrastructure company builds mission-critical inference and AI development solutions for some of the world’s most dynamic AI companies. By combining applied AI research, flexible infrastructure, and developer tooling, the organization enables companies at the forefront of artificial intelligence to bring advanced models into production.

The organization is growing rapidly and focuses on building platforms that help engineers develop, train, deploy, and operate AI products efficiently. Its Training Platform team works closely with research engineers to turn advanced AI research workflows into reliable, customer-facing products.

The organization is seeking an AI Engineer to build AI-driven product experiences for customers training and post-training frontier models. This role will also help expand the organization’s internal use of AI by transforming manual workflows into agentic systems that improve the productivity of engineering, research, and go-to-market teams.

Key Responsibilities

• Build and ship agentic product experiences, including chat-style and assistant-like interfaces, from prototype through general availability.
• Design harnesses, execution flows, and guardrails that make AI systems reliable and effective in production.
• Build internal automation and AI tooling that measurably improves the productivity of engineering, research, and go-to-market teams.
• Partner with research engineers to identify product opportunities from internal research workflows and transform them into customer-facing features.
• Define and instrument evaluations to measure whether changes improve AI output quality.
• Work across the technology stack, including API layers, backend systems, agent orchestration, and frontend applications, to deliver end-to-end features.
• Use internal training and inference products to develop a strong understanding of customer workflows and requirements.
• Identify manual processes that can be improved or replaced through AI and develop practical solutions.
• Troubleshoot bugs and resolve customer issues with urgency.
• Take ownership of AI-powered initiatives from problem identification through implementation and deployment.
• Develop reliable execution systems that enable AI agents to perform complex workflows effectively.

Required Qualifications

• 5+ years of experience building and shipping software applications.
• Demonstrated experience building and deploying AI- or LLM-powered products, agents, or agentic workflows used by real users.
• Strong software engineering fundamentals and the ability to solve complex technical problems beyond prompt engineering.
• Ability to develop accurate mental models of how AI systems, models, and supporting harnesses operate.
• Proficiency in Python and fluency in at least one additional programming language.
• Ability to work autonomously in a fast-moving environment with limited structure.
• Experience moving between customer-facing product development and internal tooling or automation.
• Strong communication skills and the ability to connect technical requirements with business needs.
• Strong ownership mentality and ability to independently identify and execute on high-impact opportunities.

Preferred Qualifications

• Experience as a founding engineer or early employee at a startup.
• Experience building evaluations, agent observability systems, or tooling for non-deterministic AI systems.
• Familiarity with agent frameworks and development tools such as LangChain, Claude Code, Codex, OpenCode, and MCP.
• Experience with model development techniques such as supervised fine-tuning, reinforcement learning, synthetic data generation, LoRA, and full model fine-tuning.
• Frontend development experience and fluency.
• Experience building production-grade AI agents and agentic workflows.
• Experience working directly with research teams to transform experimental AI systems into reliable products.

Compensation & Equity

The compensation range for this position is $220,000–$260,000, with equity opportunities. The organization aims to provide competitive compensation at or above the 90th percentile, with salary and equity grants determined based on experience and qualifications.

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