Full-Time

Member of Technical Staff

Data Platform

Posted on 1/6/2026

Contextual AI

Contextual AI

51-200 employees

Delivers enterprise-grade tailored language models

Compensation Overview

$180k - $250k/yr

+ Equity

Company Does Not Provide H1B Sponsorship

Mountain View, CA, USA

In Person

Category
Software Engineering (2)
,
Required Skills
Kubernetes
RAG
REST APIs
Requirements
  • Education: At least a Bachelor's degree in Computer Science, Software Engineering, or related field
  • Experience with Kubernetes services, distributed queuing systems, and streaming infrastructure; Proven ability to diagnose distributed vector databases and design systems for low-latency retrieval of image, text, audio, and video vectors
  • Machine Learning: Familiarity with machine learning concepts and frameworks, including dense information retrieval, document understanding/parsing models, and vision language model
  • Problem-Solving: Strong problem-solving skills and the ability to work effectively in a fast-paced, collaborative environment
  • Communication: Excellent communication and interpersonal skills, with the ability to work closely with cross-functional teams
Responsibilities
  • Design and implement scalable services, APIs, and databases to support the processing and ingestion of petabytes of information daily
  • Build and improve state-of-the-art multimodal LLMs to maximize document understanding performance
  • Design and implement comprehensive evaluation pipelines for E2E agentic RAG workflows
  • Architect and build streaming infrastructure, data orchestration systems, vector databases
  • Collaborate with ML researchers to understand state-of-the-art (SOTA) requirements for RAG systems, translating them into service specifications
  • Work directly with product managers and application engineers to understand customer requirements for end-to-end RAG systems, and translate them into technical solutions
  • Ensure seamless integration with machine learning models and pipelines, enabling efficient model deployment and management
  • Mentor and guide junior team members, promoting knowledge sharing and professional growth

Summary of Contextual AI: 1) What does the company do? Contextual.ai builds customized language models for enterprise use, delivering tailored AI solutions that integrate pre-training, fine-tuning, and alignment into a production-ready system. 2) How does the product work? It uses a pipeline that pre-trains base models, fine-tunes them on client data, and aligns components into a single integrated system to ensure production-level performance for enterprise tasks. 3) How is it different from competitors? It offers Kahneman Tversky Optimization (KTO), a method to align large language models with enterprise data cost-effectively without relying on preference data, combined with leadership from researchers from top AI institutions. 4) What is the goal? To help businesses improve workflows and decision-making by providing accurate, customized AI solutions tailored to their specific needs.

Company Size

51-200

Company Stage

Series A

Total Funding

$100M

Headquarters

San Francisco, California

Founded

2023

Simplify Jobs

Simplify's Take

What believers are saying

  • Snowflake Native App integration reaches 10,000+ enterprise customers via existing commitments.
  • Early customers Qualcomm, NVIDIA, Advantest validate production-readiness for mission-critical workflows.
  • $80M Series A at $609M valuation funds scaling across aerospace, semiconductors, manufacturing.

What critics are saying

  • OpenAI o1 surpasses GLM with 92% factuality, eroding accuracy leadership within months.
  • Google Cloud Vertex AI Agent Builder directly competes with Agent Composer using GCP lock-in.
  • NVIDIA Nemotron-4 undercuts KTO fine-tuning revenue by 40% via free CUDA integration.

What makes Contextual AI unique

  • GLM achieves 88% factuality on FACTS benchmark, outperforming GPT-4o and Claude.
  • Agent Composer reduces complex engineering tasks from hours to minutes consistently.
  • KTO alignment method eliminates preference data requirement, cutting fine-tuning costs significantly.

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Your Connections

People at Contextual AI who can refer or advise you

Benefits

Hybrid Work Options

Growth & Insights and Company News

Headcount

6 month growth

13%

1 year growth

10%

2 year growth

28%
PR Newswire
Jan 27th, 2026
Contextual AI launches Agent Composer to automate complex engineering tasks in minutes

Contextual AI has launched Agent Composer, a platform for building AI agents to automate complex engineering tasks in aerospace, semiconductors and manufacturing. The company, founded by the team that pioneered retrieval-augmented generation at Meta, has raised funding details undisclosed. Agent Composer provides infrastructure to manage context and maintain reliability across multi-step technical workflows. Users can create agents through pre-built templates, natural language descriptions or custom builds, with controls combining strict rules for critical tasks and dynamic reasoning for analysis. Early customers report significant efficiency gains: an advanced manufacturer reduced root-cause analysis from eight hours to 20 minutes, whilst a specialty chemicals manufacturer cut product research from hours to minutes. The platform is now available to enterprises including Qualcomm, Advantest, ShipBob and NVIDIA.

Cache Valley Daily
Jun 3rd, 2025
Contextual AI's State-of-the-Art Reranker Coming to Snowflake Cortex AI

SAN FRANCISCO, June 3, 2025 /PRNewswire/ - Contextual AI, the Enterprise AI company, today announced at Snowflake's annual user conference, Snowflake Summit 2025, that its state-of-the-art reranker model will be made available as a first-party model in Cortex Search.

Silicon Canals
May 28th, 2025
These Are The Richest Young Self-Made Dutch Tech Millionaires In 2025, According To Quote

In the ever-evolving world of startups and innovation, the Netherlands continues to shine as a breeding ground for young tech talent.From Amsterdam to Rotterdam, Dutch entrepreneurs are building companies that not only disrupt industries but also build personal fortunes that are nothing short of amazing.Each year, Quote magazine unveils its highly anticipated list of the Top 100 Young Self-Made Millionaires, and the 2025 edition confirms that tech remains dominant.These aren’t just early successes; these are founders building serious empires, ranging from remote work infrastructure to AI, design tools, and even crypto platforms.In this article, we have listed the 15 self-made tech millionaires from the above-mentioned list. Do have a look. Job Van Der VoortPosition: CEONet worth: €650M (8.3% increase from 2024)Remote is a global HR platform that helps companies hire, manage, and pay their entire team globally distributed workforces compliantly. With €650M to his name, and an 8.3 per cent increase from last year, Job credits the rise to solid growth “More margin, more customers, and more products — we’re almost profitable.”Job is the CEO and co-founder of Remote. He was previously a neuroscientist before becoming VP of Product at GitLab, the world’s largest all-remote company. With GitLab, he hired talent from 67 countries. Job is a sought-after presenter and often speaks about scaling a remote-first startup, remote culture, and the future of work.Douwe KielaPosition: CEONet worth: €200M (New to list)Contextual AI specialises in retrieval-augmented generation (RAG). The company’s goal is to improve how people work using artificial intelligence (AI)

Technology AI Insights
Mar 6th, 2025
Contextual AI Brings Powerful AI Insights to Snowflake with New Native App

Contextual AI, an enterprise AI leader, has launched the Contextual AI Platform as a Snowflake Native App on the Snowflake Marketplace.

VentureBeat
Mar 4th, 2025
Contextual Ai’S New Ai Model Crushes Gpt-4O In Accuracy — Here’S Why It Matters

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More. Contextual AI unveiled its grounded language model (GLM) today, claiming it delivers the highest factual accuracy in the industry by outperforming leading AI systems from Google, Anthropic and OpenAI on a key benchmark for truthfulness.The startup, founded by the pioneers of retrieval-augmented generation (RAG) technology, reported that its GLM achieved an 88% factuality score on the FACTS benchmark, compared to 84.6% for Google’s Gemini 2.0 Flash, 79.4% for Anthropic’s Claude 3.5 Sonnet and 78.8% for OpenAI’s GPT-4o.While large language models have transformed enterprise software, factual inaccuracies — often called hallucinations — remain a critical challenge for business adoption. Contextual AI aims to solve this by creating a model specifically optimized for enterprise RAG applications where accuracy is paramount.“We knew that part of the solution would be a technique called RAG — retrieval-augmented generation,” said Douwe Kiela, CEO and cofounder of Contextual AI, in an exclusive interview with VentureBeat. “And we knew that because RAG is originally my idea. What this company is about is really about doing RAG the right way, to kind of the next level of doing RAG.”The company’s focus differs significantly from general-purpose models like ChatGPT or Claude, which are designed to handle everything from creative writing to technical documentation

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