Senior AI Engineer

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

Location: San Francisco, hybrid

Employment Type: Full-time

A fast-scaling, well-funded B2B SaaS company building AI-native software for complex, high-value professional workflows.

This team is rethinking how highly skilled professionals interact with complex data, documentation, and knowledge-heavy processes. Following significant recent funding and continued commercial growth, AI has become a central part of the company’s product and engineering strategy.

Rather than adding lightweight AI features around an existing product, the engineering organization is investing heavily in the underlying platform required to make production AI reliable: evaluation, ingestion, observability, retrieval, orchestration, and the infrastructure supporting increasingly capable AI workflows.

What You’ll Do

• 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

What You’ll Bring

• Strong software engineering experience across areas such as backend engineering, distributed systems, infrastructure, developer platforms, or ML systems
• Experience shipping AI or ML systems into production rather than working exclusively on prototypes or research
• Practical experience with one or more of LLMs, RAG, NLP, AI agents, model evaluation, observability, data ingestion, or AI/ML infrastructure
• Strong understanding of software architecture, system design, reliability, and production engineering
• Ability to operate comfortably across both AI-specific problems and traditional software engineering challenges
• A high bar for engineering quality, including the ability to critically review AI-generated code rather than treating generated output as production-ready
• A pragmatic builder mentality and an appetite for high ownership in a fast-moving technical environment
• Python
• LLMs / Generative AI
• Retrieval-Augmented Generation (RAG)
• Embeddings & semantic retrieval
• LLM evaluation frameworks
• AI observability & monitoring
• Workflow orchestration
• AI / ML infrastructure
• Distributed backend systems

Why Join?

This is an opportunity to join at an important inflection point: the company has strong funding, an established product and customer base, and executive-level commitment to making AI a fundamental part of the platform.

You’ll have significant ownership over the infrastructure that determines whether AI systems actually work in production, from how information enters the system and is retrieved, through to how outputs are evaluated, monitored, and continuously improved.

About People In AI

People In AI is a specialist recruitment partner dedicated to connecting exceptional AI, Machine Learning, Data, and Software Engineering talent with some of the most ambitious technology companies in the market.

We work closely with technical founders and engineering leaders to identify opportunities where talented engineers can have genuine impact, combining deep technical understanding with a highly personalized recruitment experience.