Full-Time
Deployment Engineer
Customer Facing
Posted on 6/20/2025
LlamaIndex
51-200 employees
Connects data to large language models
Compensation Overview
$180k - $250k/yr
San Francisco, CA, USA
Hybrid
Hybrid-friendly culture based out of downtown San Francisco office.
 DevOps & Infrastructure (1) |
|---|
- 5+ years of Forward Deployed Engineer, Solutions Engineering, or similar work experience
- Experience deploying and managing various cloud deployment models, from multi-tenant SaaS to private deployments
- Experience implementing end to end DevOps or Infrastructure Engineering practices from robust CI/CD pipelines to release management best practices
- Deep experience in Docker, Kubernetes, and Terraform
- Strong coding and debugging skills in Python or Golang
- Self-starter with a strong desire to learn new things and tackle hard technical problems
- Excellent communicator with strong written and verbal communication skills, able to collaborate effectively across various engineering teams and customer personas.
- Own customer infrastructure stability from the moment they start deploying LlamaCloud to every upgrade afterwards
- Build tooling to make deployments more reliable, highly observable, and easier to debug
- Triage and troubleshoot errors in customer deployments
- Power the feedback loop between the customers and product and infrastructure teams
- Write crystal clear documentation, playbooks, or anything else that improves the overall deployment experience
- Ideate and implement solutions that exponentially increase customer happiness and drive wide-spread organization adoption.
- Hands-on experience working with large enterprises or Fortune 500 companies
- Expertise in one or more cloud providers like Azure, AWS, and GCP
- Experience with modern GitOps practices
- Experience with cloud observability tools like Grafana or Datadog
- Practical experience in general cloud network and security concepts
LlamaIndex.ai builds a data framework that helps businesses connect their own data sources to large language models (LLMs). It supports integrating structured data (like Excel and SQL), semi-structured data from APIs (such as Slack, Salesforce, and Notion), and unstructured data (web pages and images) so LLMs can understand and draw insights from a company’s data. The product works by linking diverse data sources to LLMs, enabling queries and data-driven answers across a company’s systems. Compared with competitors, LlamaIndex.ai emphasizes flexible connectors and a unified framework to access multiple data types through LLMs, making it easier for businesses to leverage AI on their existing data without heavy custom engineering. The company’s goal is to help organizations make data-driven decisions by simplifying access to their data through AI-powered language models, typically via a subscription-based B2B model.
Company Size
51-200
Company Stage
Series A
Total Funding
$27.5M
Headquarters
San Francisco, California
Founded
2023
Simplify's Take
What believers are saying
- $19M Series A from Norwest and Greylock expands 20-member team in March 2025.
- Databricks integrates LlamaIndex with MLFlow for production knowledge agents.
- KPMG investment boosts LlamaCloud adoption among 90 Fortune 500 waitlisters.
What critics are saying
- LangChain v0.3 erodes market share in 6-12 months via broader integrations.
- Databricks Mosaic AI locks customers into competing RAG workflows in 3-6 months.
- Meta Llama 4 obsoletes connectors with native RAG in Q1 2026.
What makes LlamaIndex unique
- LlamaParse delivers agentic OCR for complex documents with human-level accuracy.
- LlamaCloud processes 300+ unstructured formats into RAG-ready data at enterprise scale.
- Agent framework orchestrates multi-agent AI systems over proprietary enterprise data.
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Benefits
Health Insurance
Dental Insurance
Vision Insurance
Unlimited Paid Time Off
Company Equity
Meal Benefits
Growth & Insights and Company News
6 month growth
↓ -2%1 year growth
↑ 4%2 year growth
↑ 1%Elastic adds workflow automation for AI agents. Elastic is targeting organisations seeking to automate complex workflows using AI agents that can access and analyse enterprise data with its new Agent Builder. The platform addresses the challenge of deploying AI systems that can reliably interact with internal documents, databases and systems while maintaining governance and security controls. Agent Builder connects to Elasticsearch to retrieve enterprise data and execute automated tasks. The company claims the system "dramatically simplifies" agent development through integrated data ingestion, retrieval capabilities and built-in tools. Developers can deploy agents using multiple AI models through cloud providers. Elastic simultaneously introduced Workflows, currently in technical preview, which adds rule-based automation to supplement AI-driven decision-making. This dual approach responds to enterprise requirements for both intelligent reasoning and predictable, compliant automation - a critical consideration for organisations managing regulated data. "Agent Builder has native MCP and A2A protocol support, enabling seamless deployments within Microsoft Foundry and Microsoft Agent Framework," said Amanda Silver, corporate vice president at Microsoft CoreAI. "This gives our users a way to build context-rich, agentic AI leveraging Elasticsearch as a Knowledge Source." Elastic has partnered with Arcade.dev for agent tool integration and LlamaIndex for document processing. "Unlocking enterprise context from unstructured data sources is key to building effective agents," said Jerry Liu, CEO at LlamaIndex. The company claims its document processing capabilities will help agents "retrieve, process, and prepare data so agents can reason more accurately." Agent Builder is available in Elastic Cloud Serverless and included with the Enterprise Tier for existing customers using Elastic Cloud Hosted or self-managed deployments. Ken Exner, chief product officer at Elastic, positioned the release as addressing a gap between AI experimentation and production deployment: "By enhancing Agent Builder with Workflows, teams get a single system that delivers both intelligent reasoning and dependable automation, which is exactly what enterprises need to move from pilots to real-world impact."
Join the event trusted by enterprise leaders for nearly two decades. VB Transform brings together the people building real enterprise AI strategy. Learn moreDays after OpenAI and Google Cloud announced a partnership to support the growing use of generative AI platforms, much of the AI-powered web and tools went down due to an outage of the leading cloud providers.Google Cloud Service Platform (GCP) and some Cloudflare services began experiencing issues around 10:00 a.m. PT today, affecting several AI development tools and data storage services, including ChatGPT and Claude, as well as a variety of other AI platforms.We are aware of a service disruption to some Google Cloud services and we are working hard to get you back up and running ASAP.Please view our status dashboard for the latest updates: https://t.co/sT6UxoRK4R — Google Cloud (@googlecloud) June 12, 2025A GCP spokesperson confirmed the outage to VentureBeat, urging users to check its public status dashboard.GCP said affected services include API Gateway, Agent Assist, Cloud Data Fusion, Contact Center AI Platform, Google App Engine, Google BigQuery, Google Cloud Storage, Identity Platform, Speech-to-Text, Text-to-Speech and Vertex AI Search, among other tools. Google’s mobile development platform, Firebase, also went down.VentureBeat staffers had trouble accessing Google Meet, but other Google services on Workspace remained online.A Cloudflare spokesperson told VentureBeat only “a limited number of services at Cloudflare use Google Cloud and were impacted. We expect them to come back shortly
Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More. Google’s new AlphaEvolve shows what happens when an AI agent graduates from lab demo to production work, and you’ve got one of the most talented technology companies driving it.Built by Google’s DeepMind, the system autonomously rewrites critical code and already pays for itself inside Google. It shattered a 56-year-old record in matrix multiplication (the core of many machine learning workloads) and clawed back 0.7% of compute capacity across the company’s global data centers.Those headline feats matter, but the deeper lesson for enterprise tech leaders is how AlphaEvolve pulls them off. Its architecture – controller, fast-draft models, deep-thinking models, automated evaluators and versioned memory – illustrates the kind of production-grade plumbing that makes autonomous agents safe to deploy at scale.Google’s AI technology is arguably second to none. So the trick is figuring out how to learn from it, or even using it directly
LlamaIndex announced minority equity investments from Databricks and KPMG LLP to boost development and adoption of its LlamaCloud and LlamaParse platforms. These tools aid enterprises in building AI systems using unstructured data. Databricks and KPMG aim to enhance AI accessibility and innovation. Financial terms were not disclosed.
LlamaIndex has announced minority equity investments from Databricks and KPMG LLP, marking a key milestone in its mission to streamline the development of agentic AI solutions built on enterprise data.