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Internship Langchain Developer Jobs in California

ArangoDB

Developer Relations

San Francisco, CA · On-site +1

Both integrate seamlessly with LangChain, LlamaIndex, and MCP to amplify, not replace, existing tools. Your mission: enable developers to go from install to a working GraphRAG app on their own data ...

Prime Intellect

Internship

San Francisco, CA · On-site

... LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of ...

Arcade

Product Engineer, AI

San Francisco, CA · On-site

... with agent tooling (LangChain or equivalent custom stacks) • Technically fluent builder ... internships, startups, or open-source contributions all count • Familiarity with modern AI ...

Aembit, Inc.

AI Go-To-Market Team Intern

San Francisco, CA · Remote

$17.75 - $23.50/hr

... engineering. Your goal is to design and deploy AI-driven tools and automation workflows that help ... Build AI agents for marketing and sales use cases using frameworks like LangChain, CrewAI, or ...

Aembit

AI Go-To-Market Team Intern

San Francisco, CA · On-site

$17.75 - $23.50/hr

... engineering. Your goal is to design and deploy AI-driven tools and automation workflows that help ... Build AI agents for marketing and sales use cases using frameworks like LangChain, CrewAI, or ...

MongoDB

Senior Python Engineer

Ontario, CA · On-site +1

$123K - $166K/yr

Our mission is to increase developer adoption, satisfaction and retention by providing a reliable ... Enjoy collaborating with teammates, and mentoring junior engineers and interns * Are self-motivated ...

Avathon

AI Engineer

Pleasanton, CA · On-site

$116K - $159K/yr

... LangChain, LlamaIndex, or similar * Strong understanding of transformer architectures, LLM fine ... Experience working on applied AI projects in academic, internship, or startup settings * Interest ...

LLNL

Data Science Engineer

Livermore, CA · On-site

$121K - $154K/yr

... internships, or research projects). * Demonstrated experience developing generative AI solutions ... Experience developing AI agents or chatbot interfaces - using frameworks such as LangChain ...

LLNL

Data Science Engineer

Livermore, CA

$121K - $154K/yr

... internships, or research projects). * Demonstrated experience developing generative AI solutions ... Experience developing AI agents or chatbot interfaces - using frameworks such as LangChain ...

LLNL

Data Science Engineer

Livermore, CA · On-site

$9.7K/wk

... internships, or research projects). * Demonstrated experience developing generative AI solutions ... Experience developing AI agents or chatbot interfaces - using frameworks such as LangChain ...

OpusClip

AI Research Intern

Mountain View, CA · On-site

... context engineering strategies and Agent workflows (e.g., using LangChain, RAG frameworks ... Flexible remote/on-site internship (3 days/week required, 4+ days/week preferred). EEO OpusClip is ...

All JobsLangchain Developer JobsInternship Langchain Developer JobsInternship Langchain Developer Jobs in California

Internship Langchain Developer information

What is an internship Langchain developer?

Internship Langchain Developers are students or early-career professionals who work in a temporary, learning-focused role, specifically developing applications using LangChain, a framework for building applications powered by language models. These interns help design, code, and test solutions that integrate large language models with external data sources and tools. The role provides practical experience in AI, natural language processing, and software development while working on real-world projects. Interns often collaborate with experienced engineers and receive mentorship to develop their technical and problem-solving skills.

What are the key skills and qualifications needed to thrive as an internship Langchain developer?

To thrive as an Internship Langchain Developer, you need a solid understanding of Python programming, basic knowledge of natural language processing (NLP), and a familiarity with machine learning concepts. Experience with tools such as LangChain, OpenAI APIs, and version control systems like Git is typically required. Strong problem-solving skills, eagerness to learn, and effective communication set standout candidates apart. These skills and qualities are crucial for building effective language-based applications, collaborating with teams, and adapting to a fast-evolving AI landscape.

What kinds of projects can an internship Langchain developer expect to work on, and how do these projects contribute to skill development?

As an Internship Langchain Developer, you can expect to work on projects involving the integration of large language models (LLMs) with various data sources and APIs, such as building chatbots, automating document analysis, or developing knowledge retrieval pipelines. These projects are usually collaborative, requiring you to work closely with senior developers, data scientists, and sometimes product managers. This hands-on experience helps you develop practical skills in Python, prompt engineering, and leveraging frameworks like Langchain, while also improving your problem-solving abilities in real-world scenarios. Additionally, you’ll learn best practices for deploying and maintaining AI-powered applications, which can be valuable for pursuing advanced roles in AI development.

What is the difference between Internship Langchain Developer vs Junior AI Developer?

AspectInternship Langchain DeveloperJunior AI Developer
Required CredentialsEnrolled in or recent graduate of CS, AI, or related fieldBachelor's degree in CS, AI, or related field
Work EnvironmentInternship setting, mentorship, project-basedEntry-level position, collaborative team environment
Employer & Industry UsageTech companies, startups focusing on NLP and AITech firms, AI startups, research labs
Common Search & ComparisonYesYes

The main difference between an Internship Langchain Developer and a Junior AI Developer lies in experience level and employment status. Internships are typically temporary, mentorship-focused roles for students or recent graduates, while Junior AI Developers are entry-level full-time employees. Both roles involve working with AI and NLP technologies, but internships often emphasize learning and skill development, whereas junior roles focus on contributing to ongoing projects.

What are the most commonly searched types of Langchain Developer jobs in California? The most popular types of Langchain Developer jobs in California are:
What are popular job titles related to Internship Langchain Developer jobs in California? For Internship Langchain Developer jobs in California, the most frequently searched job titles are:
What job categories do people searching Internship Langchain Developer jobs in California look for? The top searched job categories for Internship Langchain Developer jobs in California are:
What cities in California are hiring for Internship Langchain Developer jobs? Cities in California with the most Internship Langchain Developer job openings:
Internship Langchain Developer jobs near you
Infographic showing various Internship Langchain Developer job openings in California as of August 2026, with employment types broken down into 8% Internship, 1% As Needed, 65% Full Time, 24% Part Time, 1% Temporary, and 1% Contract. Highlights an 86% Physical, 1% Hybrid, and 13% Remote job distribution.

Developer Relations

ArangoDB

San Francisco, CA • On-site, Remote

Full-time

Posted 8 days ago

Job description

Developer Relations
About Arango:
Arango delivers a unified, natively multimodel contextual data platform that powers AI agents, assistants, and applications with the unified, current, and trusted business context needed to reason, decide, and act at scale.
The Arango Contextual Data Platform connects fragmented enterprise data with LLMs, copilots, and AI agents through a simplified architecture delivered out of the box. By combining graph, vector, document, key-value, and search capabilities in a single platform, Arango eliminates the complex stacks many organizations build to operationalize enterprise AI.
Trusted by organizations including NVIDIA, HPE, the London Stock Exchange, PSI CRO, the U.S. Air Force, NIH, Siemens, Transient.AI, Matpriskollen, and Articul8, Arango helps enterprises move from AI pilots to reliable production systems faster while lowering infrastructure complexity and total cost of ownership. Arango is a proud member of the NVIDIA Inception Program and the AWS ISV Accelerate Program. Learn more at arango.ai, LinkedIn, and G2.
Location
Remote - United States preferably Bay Area location
About the Role
Step into Arango's first dedicated developer advocacy role, reporting directly to the Chief Product Officer.
Our foundation powers two breakthroughs: AutoGraph instantly builds knowledge graphs from enterprise documents, no manual ontology design required. AutoRAG dynamically selects the optimal retrieval method (GraphRAG, VectorRAG, or hybrid) for every query. Both integrate seamlessly with LangChain, LlamaIndex, and MCP to amplify, not replace, existing tools.
Your mission: enable developers to go from install to a working GraphRAG app on their own data in under 30 minutes, and to publicly demonstrate that your solution outperforms DIY alternatives.
You'll shape and build Arango's developer community, content, and event presence from scratch-defining what developer relations means here. Reporting into product (not marketing) ensures that your feedback directly shapes our roadmap, and your time is spent in the codebase, docs, and issue tracker.
Key Responsibilities
Build things developers want to copy. Create reference applications, quickstarts, and sample repositories that solve real, end-to-end problems-from multi-hop question answering over document corpora, to agents that traverse entity relationships where vector search falls short, to integrations developers can easily adopt in their projects.
Publish honest benchmarks. Acknowledge where GraphRAG excels-and where vanilla RAG outperforms it-reflecting the published literature. Run standard evaluation harnesses (like GraphRAG-Bench), publish wins, and be transparent about limitations.
Teach in public through technical posts, talks, workshops, and live builds. Prioritize depth over volume.
Engage where AI engineers already are. GraphRAG and knowledge-graph communities, AI engineering meetups, framework ecosystems, and relevant conferences-both online and in person.
Close the loop to product. Serve as the critical link between developers and our product team, delivering specific, prioritized feedback-not just general sentiment.
Skills and Experience Required
  • You are an engineer. Title aside, what matters is your ability to build and debug real, non-trivial applications.
  • You have hands-on, production experience with LLM applications and retrieval: RAG pipelines, embeddings, chunking strategies, and evaluation. You recognize that retrieval quality issues go deeper.
  • Strong Python skills, plus proficiency in at least one of TypeScript/JavaScript, Go, or Java.
  • You've written technical content that developers actually finished, and you can point us to examples.
  • You can own a room: giving talks, running workshops, or live-coding, and handle tough questions with confidence.
  • You're comfortable with Docker and Kubernetes deployments.

Strongly preferred
  • Experience with graph databases, knowledge graphs, or GraphRAG. If you've built a knowledge graph by hand, you know why AutoGraph matters.
  • Familiarity with LangChain, LlamaIndex, MCP, or similar orchestration frameworks.
  • You've run evaluation harnesses in real-world scenarios and have informed opinions about LLM-as-judge approaches.
  • Prior experience as an early or founding developer relations hire at an infrastructure or developer tools company.
  • Preferred Experience building agents at scale and for large enterprises
What Success Looks Like
  • Developers adopt and build on our reference applications and architectural blueprints.
  • A higher percentage of trial users reach a working application.
  • The roadmap shifts based on your insights from real developer feedback.
What Makes Arango Special?
At Arango, we believe that AI is only as powerful as the data foundation. Our mission is to help organizations build AI systems that can reason, decide and act based on unified, current, and trusted business context at scale. We are helping define a new category of infrastructure: the contextual data layer for AI.
Working at Arango means:
  • Contributing to cutting-edge AI and data infrastructure
  • Collaborating with experienced engineers, marketers, and product leaders
  • Helping shape how enterprises build AI-powered applications

If you're excited about the intersection of AI, data, and social media, we'd love to hear from you.

Apply