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📜 Description

  • Work directly with the platform architect and other developers to leverage deep LLM-stack expertise.
  • Build and maintain the core AI infrastructure for a platform with millions of active users.
  • Shape engineering practices as the team grows in a greenfield environment.
  • Develop production LLM-backed features, including retrieval-augmented generation and streaming responses.
  • Design and implement robust API services, ensuring high-quality performance and reliability.

🛠️ Requirements

  • 5+ years of backend engineering experience in a statically typed language (Go, Java, Kotlin, C#)
  • You've shipped production LLM-backed features — retrieval-augmented generation, streaming responses, tool use — and lived with them after launch
  • Hands-on experience with the LLM serving stack: routing across multiple model providers, failover, token streaming, and cost/usage metering
  • Experience building retrieval systems: vector search, embedding pipelines, context assembly, and citation-backed answers
  • You think in failure modes: hallucination, retrieval misses, provider outages, cost blowouts — and you build the instrumentation to catch them
  • Pragmatic about evaluation — you know how to measure whether AI answers are actually good (relevance, safety, source quality) with simple, repeatable tests, not just academic benchmarks
  • Strong API design instincts; comfortable owning a service end to end, from schema to deploy to on-call
  • US-based and authorized to work in the United States
  • Go (strongly preferred)
  • Experience with LLM gateways or serving infrastructure (LiteLLM, vLLM, TGI, or similar)
Full job description

Senior AI Engineer

Remote — US only · Full-time

Are you passionate about building AI products people actually use, serving millions of users? Do you want to help lead the AI engineering effort at this country's fastest-growing social media company that champions free speech? You'll be building AI-based features into a platform serving millions of users.

About the Role

You'll work directly with the platform architect and other developers to bring deep, hands-on LLM-stack expertise: you've built these systems before, you know where they break, and you know what "good" looks like in production.

The work is greenfield. You won't be maintaining someone else's pipeline — you'll be standing up the core AI infrastructure for a platform with millions of active users, and shaping the engineering practices around it as the team grows.

What We're Looking For

  • 5+ years of backend engineering experience in a statically typed language (Go, Java, Kotlin, C#)
  • You've shipped production LLM-backed features — retrieval-augmented generation, streaming responses, tool use — and lived with them after launch
  • Hands-on experience with the LLM serving stack: routing across multiple model providers, failover, token streaming, and cost/usage metering
  • Experience building retrieval systems: vector search, embedding pipelines, context assembly, and citation-backed answers
  • You think in failure modes: hallucination, retrieval misses, provider outages, cost blowouts — and you build the instrumentation to catch them
  • Pragmatic about evaluation — you know how to measure whether AI answers are actually good (relevance, safety, source quality) with simple, repeatable tests, not just academic benchmarks
  • Strong API design instincts; comfortable owning a service end to end, from schema to deploy to on-call
  • US-based and authorized to work in the United States

Nice to Have

  • Go (strongly preferred)
  • Python
  • Experience with LLM gateways or serving infrastructure (LiteLLM, vLLM, TGI, or similar)
  • Vector databases (Qdrant, pgvector) and embedding pipelines
  • Fine-tuning open-weight models (LoRA or full fine-tunes) and the eval discipline that goes with it
  • Content moderation or safety tooling experience• Familiarity with Ruby on Rails or React/TypeScript (you'll integrate with both)

Our Stack

Go, Ruby on Rails, Python, React/TypeScript, PostgreSQL, Redis, RabbitMQ. Services deployed across multiple data centers.

Why TMTG?

We are a social media company dedicated to delivering users an engaging and censorship-free experience. We believe users should be able to freely express themselves and engage with a rich diversity of viewpoints on a cancel-proof, accessible platform. If you are interested in joining a company that is fast-paced, rapidly growing, and committed to free speech, please get in touch.

Equal Employment Opportunity

Our Company is an equal opportunity employer that prohibits discrimination and harassment on the basis of any protected characteristic as outlined by federal, state, or local laws.

This policy applies to all employment practices within our organization, including hiring, recruiting, promotion, termination, layoff, recall, leave of absence, compensation, benefits, training, and apprenticeship. Our Company makes hiring decisions based solely on qualifications, merit, and business needs at the time.

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