Staff Applied AI Engineer
(LLM Systems, Memory & Evaluation)
Compensation: $250,000 - $300,000 + Equity
Location: Remote — US / Canada | Hybrid available in New York or Toronto
The Company
A rapidly scaling, venture-backed enterprise AI company is building conversational AI technology designed to transform how people learn, develop and receive personalized support at work. With significant adoption across global enterprises, the company is entering an important stage of product and technical growth.
Its platform combines advanced language models with enterprise context, personalization and intelligent workflows to deliver meaningful AI-powered experiences at scale.
The Opportunity
This is an opportunity to help shape the intelligence behind a production AI platform used within major organizations.
The business is looking for engineers who want to go beyond integrating LLM APIs and take genuine ownership of how AI systems reason, remember, evaluate and improve. You'll work on difficult applied AI problems with the freedom to experiment and the responsibility to deliver reliable production capabilities.
The Role
As a Senior / Staff Applied AI Engineer, you'll design and build the AI systems powering sophisticated conversational experiences.
You'll own capabilities across context engineering, retrieval, memory, evaluation and model orchestration, taking ideas from emerging research and new model releases into production.
At Staff level, you'll also influence technical architecture, establish engineering standards and help guide the broader direction of the AI platform.
What You’ll Do
Build and improve production LLM systems incorporating context retrieval, long-term memory, personalization and agentic workflows.
Design evaluation frameworks and feedback loops measuring conversation quality, groundedness, safety and user experience.
Experiment with frontier models and emerging techniques, identifying where they deliver measurable product improvements.
Develop orchestration and prompting strategies that improve AI reasoning, reliability and efficiency.
Optimize AI systems for production performance, latency, cost, observability and scalability.
Collaborate with Product, Engineering and Design to translate user needs into intelligent product capabilities.
At Staff level, provide architectural direction and technical leadership across teams while remaining hands-on.
What You’ll Bring
6+ years of software engineering or machine learning engineering experience.
At least 2 years building and shipping LLM-powered capabilities into production.
Strong Python skills and experience developing reliable backend or ML systems.
Practical knowledge of modern LLM architectures, retrieval, prompting, tool use and agentic workflows.
Experience evaluating or improving the quality and reliability of real-world AI applications.
Ability to independently identify technical opportunities, experiment rapidly and deliver measurable improvements.
Strong communication skills and the ability to work effectively across engineering and product stakeholders.
What This Role Requires
Demonstrable ownership of production LLM systems used by real customers.
Strong hands-on engineering capability, with an understanding of how modern AI applications are designed and deployed.
Ability to make informed technical tradeoffs across quality, performance, reliability and cost.
For Staff-level candidates, evidence of influencing technical direction and raising engineering standards beyond individual projects.
Tech Stack
Python and production backend services.
Large language models, including experimentation with OpenAI, Anthropic and other providers.
Prompt engineering, context engineering and retrieval systems.
Agentic workflows, tool use and model orchestration.
AI evaluation, automated graders, observability and regression testing.
Experience with Azure AI, fine-tuning or real-time voice systems is advantageous.
Why Join
Real AI engineering challenges: Work on context, memory, personalization and evaluation problems that directly affect how people experience conversational AI.
Ownership and technical influence: Build core capabilities, shape technical decisions and help determine which emerging AI technologies make it into production.
Commercial momentum with meaningful impact: Join a scaling AI company with established enterprise demand, ambitious technical plans and a product focused on helping people develop professionally.
About People in AI
People in AI is a specialist recruitment partner connecting exceptional AI, machine learning, data, and engineering talent with some of the most ambitious technology companies in the world. We work closely with founders, technical leaders, and hiring teams to represent opportunities accurately and help candidates assess genuine fit.
