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Langgraph Jobs in Rancho Cucamonga, CA (NOW HIRING)

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Langgraph information

What is a Langgraph?

Langgraph is a framework designed to build, manage, and orchestrate complex workflows for large language models (LLMs). It allows developers to create directed graphs of language model prompts, tools, and custom logic, making it easier to design multi-step, stateful AI applications. Langgraph is especially useful for building conversational agents, automated workflows, and other applications that require LLMs to interact with data or tools in a structured way.

What are some common challenges faced by Langgraph developers when integrating their workflow with existing AI infrastructure?

Langgraph developers often encounter challenges when integrating their workflow with existing AI infrastructure, such as ensuring compatibility with various large language models and managing data flow across multiple APIs. Coordination with data engineers and machine learning specialists is crucial to align model outputs with business requirements, and adapting to rapidly evolving technologies can require continuous learning. Additionally, optimizing performance and maintaining security standards during integration are key considerations to ensure successful deployment.

What are the key skills and qualifications needed to thrive as a Langgraph engineer, and why are they important?

To thrive as a Langgraph engineer, you need a strong background in software engineering, proficiency in Python, and a solid understanding of AI/ML concepts, usually supported by a degree in computer science or a related field. Familiarity with machine learning frameworks (like TensorFlow or PyTorch), API integrations, and version control systems such as Git is essential. Effective problem-solving, collaboration, and clear communication are crucial soft skills for working with multidisciplinary teams and resolving complex issues. These capabilities are important because they enable the development, scaling, and maintenance of robust AI-driven applications using the Langgraph platform.

What is the difference between Langgraph vs Data Analyst?

AspectLanggraphData Analyst
Required CredentialsTypically requires knowledge of language processing and graph databasesUsually requires a degree in statistics, mathematics, or related fields
Work EnvironmentTech companies, AI research labs, data-driven organizationsBusiness, finance, healthcare, and marketing sectors
Industry UsageEmerging role in AI and NLP projectsEstablished role in data interpretation and reporting

While Langgraph focuses on language processing and graph database integration, Data Analysts primarily interpret and visualize data to support business decisions. Both roles require analytical skills, but Langgraph specialists often have a background in AI and NLP, whereas Data Analysts typically hold degrees in statistics or related fields.

What are popular job titles related to Langgraph jobs in Rancho Cucamonga, CA?

For Langgraph jobs in Rancho Cucamonga, CA, the most frequently searched job titles are:

What job categories do people searching Langgraph jobs in Rancho Cucamonga, CA look for?

The top searched job categories for Langgraph jobs in Rancho Cucamonga, CA are:

What cities near Rancho Cucamonga, CA are hiring for Langgraph jobs?

Cities near Rancho Cucamonga, CA with the most Langgraph job openings:

Langgraph jobs near you
Infographic showing various Langgraph job openings in Rancho Cucamonga, CA as of August 2026, with employment types broken down into 67% Full Time, and 33% Contract. Highlights an 82% In-person, and 18% Remote job distribution.

Manager, AI Innovation and Solutions

PSB Insights

Whittier, CA • On-site

$70K - $119K/yr

Full-time

Medical, Dental, Vision, Life, Retirement

Re-posted 13 hours ago

Job description

Location: Hybrid (onsite 2-3 days/week in Whittier, CA)

Status: Contract to Hire

Reports To: VP, Unstructured Data Analytics & AI Innovation

Role Overview

PSB Insights is seeking a contract to hire Manager, AI Innovation and Solutions to lead the charge in defining "what's next" for our advanced research and data analytics capabilities. This role sits at the intersection of AI product engineering, advanced unstructured data analytics, and strategic research. You will not only apply cutting-edge methodologies to solve high-impact client engagements but will actively architect, build, and deploy custom agentic AI systems, automated workflows, and data products and solutions.

The ideal candidate is a builder, a hands-on developer, and a strategic thinker. You possess deep technical expertise in Python, R, and SQL, and have a proven track record of designing and implementing agentic workflows (e.g., multi-agent systems, tool-use LLMs, autonomous research loops) within cloud environments - specifically Google Cloud Platform (GCP) and Azure. You know how to design human-in-the-loop workflows.

We are looking for an applied AI developer who can lead complex initiatives, converting highly ambiguous business questions into scalable technical architectures and turn emerging AI capabilities into practical, reliable products and workflows. This role is not focused on training foundation models; but, rather, it is focused on selecting, integrating, evaluating, and orchestrating existing models to solve real business and research problems.

Key Responsibilities:

AI Innovation & Solution Development

  • Agentic AI Engineering: Architect, prototype, and build custom agentic workflows, tool-calling systems, and multi-step AI applications to automate, scale, and deeply enrich qualitative and quantitative research processes.
  • Product & Solution Building: Lead the end-to-end development of proprietary AI-driven tools, custom APIs, and analytics products that differentiate PSB’s capabilities in the market. Manage structured outputs, function calling, JSON schemas, and API orchestration.
  • Cloud Architecture (GCP and Azure): Deploy, manage, and optimize AI models, databases, and data pipelines utilizing Google Cloud Platform and Azure services (e.g., Vertex AI, Microsoft Foundry, etc.).
  • Research & Development: Investigate and explore emerging AI frameworks, LLMs, vector databases, and NLP techniques, rapidly translating academic or industry breakthroughs into production-ready business solutions. Integrate LLMs through APIs, including OpenAI, Anthropic, and Google models, into client-facing applications and internal workflows.

Advanced Analytics & Data Engineering

  • Multi-Engine Programming: Write, optimize, and maintain production-grade code in Python and R for advanced text/image/video processing, statistical modeling, machine learning, and data visualization. Develop AI solutions using modern machine learning frameworks, including the Hugging Face ecosystem.
  • Database & Query Design: Architect structured databases and write highly complex SQL queries to extract, clean, and merge diverse datasets (first-party surveys, social data, digital scraping, and client databases).

Project Leadership & Client Strategy

  • Methodology Standardization: Establish and champion best practices for code reproducibility, analytical rigor, data security, quality assurance, and documentation across the team. Utilize modern software development practices, including Git/GitHub for version control and Agile methodologies for project delivery.
  • Collaboration: Partner closely with data scientists, project managers, and senior leadership, providing technical mentorship where needed.

Candidate Profile:

Technical Requirements

  • Applied AI Engineering: Advanced Python skills, with hands-on experience building AI-enabled applications, agentic workflows, tool-calling systems, structured outputs, APIs, and human-in-the-loop processes using models from OpenAI, Anthropic, Google, or Microsoft.
  • Agent and Integration Technologies: Experience with LLM orchestration frameworks and protocols such as LangGraph, LangChain, LlamaIndex, Semantic Kernel, AutoGen, and Model Context Protocol (MCP), including connecting agents to databases, APIs, enterprise systems, and external tools.
  • Modern Data Stack: Strong SQL skills and experience with cloud data platforms such as Databricks, BigQuery, or Microsoft Fabric, including structured, unstructured, and vector data architectures, data pipelines, and workflow orchestration.
  • Cloud and Product Deployment: Experience building and deploying secure, production-ready AI applications on GCP and/or Azure using tools such as Vertex AI, Cloud Run, Microsoft Foundry, Azure Functions, Docker, Git/GitHub, and CI/CD workflows.
  • AI Quality, Security, and Retrieval: Experience with RAG, embeddings, vector and hybrid search, reranking, LLM evaluation, tracing, monitoring, prompt and model versioning, access controls, data privacy, prompt-injection mitigation, and production testing.
  • R and Survey Data Engineering: Experience using R for survey-data ETL, supporting reusable internal libraries or packages, and maintaining production analytical workflows.

Experience & Education

  • Education: Bachelor’s degree in quantitative, computational, or scientific discipline (e.g., Computer Science, Data Science, Statistics, Economics, Engineering). An advanced degree with research experience is a bonus.
  • Experience: 3+ years of professional experience in data science, AI engineering, analytics, or market research, with a minimum of 2 years specifically focused on building or developing AI solutions, digital products, or NLP pipelines.
  • Proven Portfolio: A portfolio of built products, open-source contributions, custom dashboards, or published research showcasing your ability to take a solution from concept to functional product.

Professional Competencies

  • Structured Problem Solving: Exceptional ability to translate highly ambiguous, complex client business problems into step-by-step logic and robust technical workflows.
  • Strategic Communication: An innate ability to explain "how the black box works" to non-technical stakeholders in a highly persuasive, visual way.
  • Agility & Curiosity: A passionate self-starter who actively experiments with new AI models and thrives in a fast-paced, rapidly evolving hybrid environment.

Why PSB Insights

Within PSB, we’re building what’s next. Our PSB Labs team sits at the forefront of how we evolve research - leveraging AI-engineered approaches, agentic workflows, and cloud-native solutions to unlock insights from massive, chaotic datasets. When traditional methods aren’t enough, this team pioneers new ways forward.

At PSB, you will have the unique opportunity to act as both a technical founder and an executive consultant - building proprietary systems while immediately seeing their impact on some of the world's most influential brands.

Benefits

  • Healthcare, dental, vision, FSA, life insurance, short- and long-term disability, and pet insurance
  • 401(k) with generous employer match
  • Flexible Time Off (FTO)
  • End of Year Holiday Office Closure
  • Paid parental leave after 12 months
  • Modern office locations with premium hybrid amenities

PSB Insights is an equal opportunity employer and values diversity of thought, background, and experience. The anticipated annual base salary range for this position is $70,000–$119,000 USD, depending on qualifications, geography and experience. In addition to base salary, PSB offers a comprehensive benefits package and opportunities for incentive compensation, where applicable.

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