AI role · Open offer

LLM Engineer — RAG & embeddings

Cohere

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At a glance

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

Employment: Full-time
Workplace: Hybrid
Location: 115 Broadway, New York, NY 10006, United States · Hybrid
Compensation: $175k–$230k + equity
Experience level: Senior
Team: Applied LLM
Benefits & perks

About this role

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

Cohere builds enterprise LLM APIs with strong retrieval and multilingual support. NYC engineering owns core model serving and developer experience.

LLM Engineer — RAG & embeddings (New York): chunking, rerankers, eval suites, and latency SLOs for API customers.

What you will do

Ship production enterprise RAG APIs with clear evaluation, monitoring, and rollback paths—not demo-only notebooks.
Partner with product, design, and domain experts on requirements, trade-offs, and safe rollout.
Improve data quality, labeling, and offline metrics that correlate with business KPIs.
Document architectures and runbooks for on-call and customer-facing teams.
Mentor engineers on testing, observability, and responsible AI practices.

What we look for

Strong Python and modern ML/LLM stack experience with multiple shipped features.
Comfort with SQL, experimentation, and communicating results to non-technical stakeholders.
Pragmatic ownership from prototype to production—including cost and latency budgets.
Eligible to work in the listed country; professional English (French a plus for Paris roles).

Skills we're hiring for

Core capabilities—LLMs, automation, analytics, product, or domain expertise.

PythonLangChainOpenAI API

Tools & stack

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

Vector DBs

You're a strong fit if…

You've shipped real work with AI—not only experimented in isolation.
Several listed skills or tools show up in your recent projects.
You can explain trade-offs (quality, cost, latency, safety) in plain language.

Apply

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What the employer asked for

RAG latency or quality win you can quantify.

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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Regulated RAG rollout
Multi-tenant pipeline: chunking, ACL-aware retrieval, audit logs, and human approval for outbou…
Demo Repo Link
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Top skills

Python

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