Senior AI Platform Engineer (Hybrid)

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

Job summary

People In AI in San Francisco is seeking a senior AI platform engineer to build production-grade AI infrastructure and own end-to-end AI systems from ingestion to deployment.

You will design RAG pipelines, embeddings, and model interactions, and work closely with product, design and engineering to deliver usable AI workflows. You will also contribute to observability and reliability across systems.

Qualifications

• Experience shipping AI/ML systems to production.
• Strong software engineering with backend/distributed systems.
• Understanding of AI/ML infrastructure and observability.
• Ability to work across AI and traditional software challenges.

Responsibilities

• Build and scale core AI platform capabilities across evals, ingestion, observability, retrieval, and AI/ML infrastructure.
• Own AI systems end-to-end, taking ideas from prototype through to reliable production deployments.
• Design and improve RAG pipelines, embedding workflows, prompt systems, retrieval strategies, and model interaction patterns.
• Develop infrastructure for evaluating, monitoring, versioning, and improving LLM-powered systems.
• Build tooling around AI workflow orchestration, quality control, experimentation, and production reliability.
• Work with complex, domain-specific datasets to improve retrieval and model performance.
• Partner closely with product, design, engineering, and subject-matter experts to turn sophisticated workflows into usable AI products.
• Help establish technical patterns and engineering standards for applied AI across the wider organization.

Skills

Backend engineering

Distributed systems

Infrastructure

ML systems

Python

LLMs / Generative AI

RAG

Embeddings & semantic retrieval

AI observability & monitoring

Workflow orchestration

AI / ML infrastructure

Distributed backend systems

Job description

People In AI in San Francisco is seeking a senior AI platform engineer to build production-grade AI infrastructure and own end-to-end AI systems from ingestion to deployment.

You will design RAG pipelines, embeddings, and model interactions, and work closely with product, design and engineering to deliver usable AI workflows. You will also contribute to observability and reliability across systems.