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AI role · Open offer

Senior LLM Engineer — conversational AI (Remote US)

Twilio

Full-time
Senior
Customer AI
Remote
Remote · United States
Remote, United States
$170k–$230k + equity

This listing is optimized for AI-native talent: clear skills and tools so candidates know if they fit before they apply—and so you spend less time screening mismatches.

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At a glance

How you'll work, where, and key listing dates.

Employment: Full-time
Workplace: Remote
Location: Remote · United States
Compensation: $170k–$230k + equity
Experience level: Senior
Team: Customer AI
Benefits & perks: All-remote US, equity, home office stipend.
How to apply: Voice/chat LLM agents with latency SLOs and enterprise guardrails.
Company site: www.twilio.com
Listed: Jul 14, 2026
Updated: Aug 3, 2026

About this role

What the team is looking for and how this position fits.

Twilio is hiring a Senior Senior LLM Engineer — conversational AI (Remote US) on the Customer AI team (Remote · Remote, United States). This is a hands-on role in LLM & generative AI—not a generic “AI enthusiast” post.

You will own LLM features, retrieval, agents, and evaluation end to end: problem framing, offline evaluation, safe rollout, and iteration from production signals. Success is measured with clear metrics (quality, latency, cost, or business KPIs)—not slide decks alone.

Twilio powers customer engagement APIs — voice, SMS, email, and AI agents — used by millions of developers worldwide.

Senior LLM Engineer (Remote US): build conversational agents, agent assist, and knowledge retrieval for contact centers with strict latency and compliance needs.

About Twilio

Public cloud communications company; AI is central to Flex and Segment.
Enterprise customers require HIPAA/PCI-aware architectures.
Remote-first US engineering with global customers.

What you will do

Ship streaming LLM pipelines for voice and chat channels.
Build evals for containment, escalation, and hallucination rates.
Integrate tool-calling with CRM and ticketing systems.

Stack & environment

Python, LangChain, NLP APIs, AWS.
Fully remote United States.

What we look for

Production conversational AI; voice experience valued.
US work authorization required.

Skills we're hiring for

What each capability means for this role—not a keyword checklist.

Python
Production Python for data pipelines, model code, APIs, and automated tests—not notebook-only workflows.
LangChain
Orchestrating LLM chains, tools, and retrieval with observable steps and failure handling.
OpenAI API
Calling frontier APIs with retries, cost controls, prompt versioning, and safety filters.
NLP
Text pipelines: tokenization, fine-tuning, evaluation, and guardrails for user-facing language features.

Tools & stack

Platforms and products mentioned for this role (APIs, IDEs, vector DBs, CRMs, design tools, etc.).

AWSTool
Regular use of AWS in the LLM & generative AI stack—configuration, debugging, and team conventions.
DockerTool
Containerized services and reproducible dev environments for ML and LLM workloads.

You're a strong fit if…

Tailored to this listing—use it as a self-check before you apply.

You can show evidence in your application: Voice/chat LLM agents with latency SLOs and enterprise guardrails.
Several of these show up in recent shipped work—not only on your CV: Python, LangChain, OpenAI API, NLP, and AWS.
You have owned LLM features, retrieval, agents, and evaluation in production: debugging live issues, running postmortems, and iterating from real user or business signals.
You communicate clearly in writing, document decisions, and can overlap with the team’s core hours for pairing and incident response.
You explain trade-offs (quality, cost, latency, safety) in plain language—with numbers or examples, not buzzwords.
You read the full listing (comp: $170k–$230k + equity, benefits in At a glance) and your expectations align.

Apply

Candidate accounts only: add your headline and bio on My account, and optionally a CV link or PDF so recruiters see your full résumé. Then write a short pitch below—applications use your login email.

What the employer asked for

Voice/chat LLM agents with latency SLOs and enterprise guardrails.

Sign in with a candidate account to apply

Register, add a headline and bio, then you can attach a CV link or PDF on My account before you apply. That keeps applications tied to your profile and makes it easier for employers to review your background.

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