Staff Applied AI Engineer — Build Enterprise LLMs (Remote)

People in AI; United States; Hybrid; USD 250,000 - 300,000; Full time

Job summary

People in AI is hiring a Staff Applied AI Engineer to shape the intelligence behind its enterprise AI platform. You will own production LLM systems, retrieval, memory, and personalization, with significant ownership over architecture and product quality.

You will lead the design and deployment of agentic workflows, orchestration, and evaluation frameworks while collaborating with product and design teams to deliver scalable, safer AI solutions for large organizations.

Qualifications

• 6+ years in software or ML engineering.
• 2+ years building production LLM applications.
• Strong Python skills.
• Experience with retrieval, context engineering, LLM orchestration, or agentic systems.
• Understanding of LLM evaluation, model limitations, and production quality.
• Proven ownership of AI systems beyond prototypes.
• Ability to assess new AI technologies and make sound architectural decisions.
• Strong technical leadership, communication, and startup‑minded ownership.

Responsibilities

• Build and improve LLM-powered systems for context, memory, retrieval, and personalization.
• Develop agentic workflows and orchestration architectures.
• Design evaluation frameworks measuring accuracy, quality, safety, and reliability.
• Experiment with frontier models and bring new AI capabilities into production.
• Optimize production systems for performance, latency, cost, and scalability.
• Influence AI architecture, technical direction, and engineering best practices.
• Collaborate with Product, Engineering, and Design to improve user experience.

Skills

Production LLMs

Python

Retrieval

Context engineering

Orchestration

Architectural decisions

Leadership

Job description

People in AI is hiring a Staff Applied AI Engineer to shape the intelligence behind its enterprise AI platform. You will own production LLM systems, retrieval, memory, and personalization, with significant ownership over architecture and product quality.

You will lead the design and deployment of agentic workflows, orchestration, and evaluation frameworks while collaborating with product and design teams to deliver scalable, safer AI solutions for large organizations.