Principal AI Engineer

People In AI; San Francisco (CA); Hybrid; USD 180,000 - 240,000; Full time

Job summary

People In AI is seeking a principal-level engineer to define how production AI systems are designed, evaluated, monitored, and scaled across the company. You will have broad technical ownership of a platform central to the next phase of the product roadmap.

The role combines hands-on engineering with technical leadership, setting standards and guiding multidisciplinary teams from prototypes to durable customer-facing systems, focusing on evaluation, observability, retrieval, and reliability.

Qualifications

• Deep software engineering experience across backend systems, infrastructure, distributed systems, or platform engineering.
• Experience shipping AI or ML systems into production.
• Strong Python skills and ability to engage in rigorous coding and system design discussions.
• Experience with LLMs, retrieval, agents, NLP, evaluations, observability, or data ingestion.
• Ownership mindset to lead technically without formal management authority.
• Excellent communication across engineering, product, design and business teams.

Responsibilities

• Architect and scale the company’s core AI platform and supporting infrastructure.
• Build evaluation frameworks, monitoring systems, ingestion pipelines, and observability tooling for production AI applications.
• Design and improve retrieval, embedding, prompting, and model-interaction workflows.
• Lead AI projects from experimentation through deployment, measurement, and ongoing optimization.
• Establish engineering standards for testing, versioning, quality control, and system reliability.
• Partner with product, design, engineering, and domain specialists to translate complex workflows into effective AI products.
• Provide technical direction and raise the quality of AI engineering across the wider organization.

Skills

Backend systems

Infrastructure

Distributed systems

Platform engineering

AI in production

Python

LLMs

Retrieval systems

NLP

Observability

Data ingestion

Job description

San Francisco Hybrid (2 days a week)

The Company

A high-growth, venture-backed SaaS company is building AI-powered products for complex, knowledge-intensive workflows. The business has established market traction and is making a significant investment in the infrastructure required to deliver reliable applied AI at scale.

The Opportunity

This is a principal-level opportunity to help define how production AI systems are designed, evaluated, monitored, and scaled across the company. You will have broad technical ownership and direct influence over a platform that is central to the next phase of the product roadmap.

The Role

You will architect and build the infrastructure behind production LLM applications, with a focus on evaluation, ingestion, observability, retrieval, and operational reliability. You will combine hands-on engineering with technical leadership, setting standards and helping multidisciplinary teams move from prototypes to durable customer-facing systems.

What You’ll Do

• Architect and scale the company’s core AI platform and supporting infrastructure.
• Build evaluation frameworks, monitoring systems, ingestion pipelines, and observability tooling for production AI applications.
• Design and improve retrieval, embedding, prompting, and model-interaction workflows.
• Lead AI projects from early experimentation through deployment, measurement, and ongoing optimization.
• Establish engineering standards for testing, versioning, quality control, and system reliability.
• Partner with product, design, engineering, and domain specialists to translate complex workflows into effective AI products.
• Provide technical direction and raise the quality of AI engineering across the wider organization.

What You’ll Bring

• Deep software engineering experience across backend systems, infrastructure, distributed systems, or platform engineering.
• A track record of shipping AI or machine learning systems into production.
• Strong Python skills and the ability to perform well in rigorous coding and system design discussions.
• Experience with areas such as LLMs, retrieval systems, agents, NLP, evaluations, observability, or data ingestion.
• The judgement to balance experimentation, delivery speed, technical quality, and long-term maintainability.
• A high-ownership approach and the ability to lead technically without relying on formal management authority.
• Clear communication skills and confidence working across engineering, product, design, and business teams.

What This Role Requires

• Production experience building or operating AI-enabled software systems.
• Strong backend or platform engineering fundamentals.
• Ability to design and own complex systems from initial architecture through production operation.
• Willingness to work on-site in San Francisco.

Why Join

• Own a strategically important AI platform with company-wide product impact.
• Solve complex production challenges across evaluation, reliability, retrieval, data, and infrastructure.
• Join during a major scaling phase with strong compensation, equity, and meaningful technical influence.