Senior Product Engineer (AI)

Senior Product Engineer (AI) to build AI infrastructure and features, own problems end-to-end, and drive system scalability in a hybrid London office.

Plain is redefining customer support for the next generation of B2B companies. We’re building the fastest, most powerful platform to help companies move beyond reactive support and build true customer relationships.

Some of the world’s most forward-thinking companies - like Cursor, Raycast, and Granola - trust Plain to unify all customer interactions, enable faster team collaboration, and supercharge their workflows with AI.

B2B customer support is undergoing a seismic shift. AI is transforming the way companies engage with customers, shifting support from a siloed function to a company-wide effort across Slack, Discord, and any other channel you talk to customers in. The old way - slow, manual, and disconnected - no longer works.

This role is hybrid with 3 days a week in our {#location}London office{/location}.

What you’ll do

We’re in a rare spot. Plain is already powering support for high-growth companies with a lightning-fast, deeply scalable platform. AI has been part of our DNA from the start. Now we’re doubling down to define how it shapes every layer of modern customer support.

This is where you come in.

We're looking for a customer obsessed Senior Product Engineer to help take our AI ambitions to the next level. You’ll build the Infrastructure that helps us build AI features quickly, safely and with confidence. You’ll own problems end to end, and play a key role in building a category-defining product.

In this role, you will:

Own and ship AI features such as our agents, assistants, insights and more - from concept to production.
Design and implement backend services for AI integrations and data pipeline.
Build robust APIs and abstractions for internal AI usage
Drive system scalability: caching, optimization, processing patterns, etc
Contribute and drive the evolution of the infrastructure for AI including architecture, evaluation and iteration pipelines.
Solve complex AI challenges around AI accuracy, reliability, and quality – using rigorous quantitive approaches.
Advocate for our work externally – writing, speaking, and engaging with the broader AI community.

This is a great fit if you…

Are an experienced backend engineer who’s shipped AI products in the OpenAI & Anthropic era – especially text and data-heavy AI applications.
Have hands-on experience with LLM orchestration and LLM API optimization (costs, latency, etc)
Are familiar with RAG architectures and technologies
Have AI observability experience. AI isn’t just about shipping features that sound great – it’s about knowing, conclusively, if they’re making things better.
Have a clear perspective on what makes a great AI product. We want to apply AI with precision, nuance, and real impact – not as a gimmick.
Are product minded and customer focused in how you build software.
Measure your success by user impact, not just technical elegance.
Are self-driven, impact-focused, and thrive in a fast-moving, high-ownership environment.
Bonus: you have experience with agent frameworks and design.

This won’t be the right role if you…

Have primarily academic or research ML/AI experience. This role’s looking for someone with Applied AI experience.
Think AI for support is just chatbots and deflection. B2B support is complex – we want AI through the platform, not just automating conversations.
Struggle with ambiguity. We’re an early-stage startup. Things change quickly, and often, knowing what to work on is as important as the work itself.
Prioritize working with the latest tech for its own sake. We choose tools that make us productive – not what’s trendy. (Postgres is great.)
Are looking for a management role. This is a hands-on individual contributor position.
Want the perks of a big company. We offer competitive compensation for our stage, but we’re a startup – this is a different kind of opportunity.

What you’ll do

This is where you come in.

In this role, you will:

Own and ship AI features such as our agents, assistants, insights and more - from concept to production.

Design and implement backend services for AI integrations and data pipeline.

Build robust APIs and abstractions for internal AI usage

Drive system scalability: caching, optimization, processing patterns, etc

Contribute and drive the evolution of the infrastructure for AI including architecture, evaluation and iteration pipelines.

Solve complex AI challenges around AI accuracy, reliability, and quality – using rigorous quantitive approaches.

Advocate for our work externally – writing, speaking, and engaging with the broader AI community.

This is a great fit if you…

Are an experienced backend engineer who’s shipped AI products in the OpenAI & Anthropic era – especially text and data-heavy AI applications.

Have hands-on experience with LLM orchestration and LLM API optimization (costs, latency, etc)

Are familiar with RAG architectures and technologies

Have AI observability experience. AI isn’t just about shipping features that sound great – it’s about knowing, conclusively, if they’re making things better.

Have a clear perspective on what makes a great AI product. We want to apply AI with precision, nuance, and real impact – not as a gimmick.

Are product minded and customer focused in how you build software.

Measure your success by user impact, not just technical elegance.

Are self-driven, impact-focused, and thrive in a fast-moving, high-ownership environment.

Bonus: you have experience with agent frameworks and design.

This won’t be the right role if you…

Have primarily academic or research ML/AI experience. This role’s looking for someone with Applied AI experience.

Think AI for support is just chatbots and deflection. B2B support is complex – we want AI through the platform, not just automating conversations.

Struggle with ambiguity. We’re an early-stage startup. Things change quickly, and often, knowing what to work on is as important as the work itself.

Prioritize working with the latest tech for its own sake. We choose tools that make us productive – not what’s trendy. (Postgres is great.)

Are looking for a management role. This is a hands-on individual contributor position.

Want the perks of a big company. We offer competitive compensation for our stage, but we’re a startup – this is a different kind of opportunity.