Staff Applied AI Engineer

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

High-Growth Enterprise AI Company | Remote US & Canada / Hybrid NYC or Toronto

Compensation: $250,000–$300,000 USD Base + Equity

About the Company

We're partnering with a fast-growing, venture-backed AI company transforming how large organizations support and develop their employees.

Its enterprise AI platform delivers personalized, context-aware coaching, leveraging LLMs, organizational data, and advanced AI capabilities to create meaningful interactions at scale.

With 100+ enterprise deployments, nearly $45M in ARR, and backing from leading investors, the company is entering an exciting growth phase and expanding its Applied AI team.

The Opportunity

The company is hiring a Staff Applied AI Engineer to help shape the intelligence behind its core AI platform.

You’ll work on production LLM systems, retrieval, memory, personalization, and agentic workflows, with significant ownership over technical architecture and product quality.

This is a hands‑on, high‑impact role for an engineer who combines strong ML expertise with production engineering skills and a passion for advancing frontier AI capabilities.

What You’ll Do

• 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.

What We’re Looking For

• 6+ years in software or ML engineering, including 2+ years building production LLM applications.
• Strong Python skills and practical ML engineering expertise.
• 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 or proofs-of-concept.
• Ability to assess new AI technologies and make sound architectural decisions.
• Strong technical leadership, communication, and startup‑minded ownership.

Nice to Have

• Experience building LLM evaluation frameworks or feedback loops.
• Exposure to conversational AI, personalization, or long-term memory systems.
• Experience at a high‑growth startup or AI‑native company.
• Familiarity with frontier models, agent architectures, and model optimization.

Python, LLMs, retrieval systems, context engineering, AI agents, and evaluation infrastructure.

You’ll help shape the broader AI architecture while working with emerging models and production AI technologies.

Why Join?

• Core AI ownership: Shape how an enterprise AI product reasons, remembers, and personalizes interactions.
• Strong traction: 100+ enterprise deployments and rapidly growing recurring revenue.
• Frontier AI exposure: Experiment with new models and bring advanced capabilities into production.
• Technical influence: Drive architectural decisions and raise engineering standards.
• Meaningful impact: Build AI technology used to support employee development across major global organizations.
• Remote flexibility: Work remotely across the US or Canada.