langgraph jobs in San Diego

Lead enterprise generative AI architecture and solution design on Oracle Cloud Infrastructure (OCI), focusing on agentic workflows, retrieval-augmented generation pipelines, and Oracle application integrations. Define governance, security, and compliance standards for AI/ML initiatives across the enterprise.…See more Mentor delivery teams on prompt engineering, model selection, and optimization; identify high-value AI use cases and guide pilot deployments that drive business outcomes.

As L3 production support lead for ClaimBeacon, a Guidewire-integrated agentic AI platform, you'll own end-to-end troubleshooting and resolution of production bugs, data pipeline failures, AI agent issues, and small enhancements across the full stack (Java, Python, Flutter). You'll reproduce issues using logs and monitoring tools, decide what escalates to core engineering, and ensure fixes maintain data/AI governance and compliance standards.…See more The role requires 5+ years of software engineering or production support experience with proven end-to-end ownership of production issues, plus comfort working across frontend, backend, data, and infrastructure in a live, high-pressure environment.

This role blends technical presales engineering with hands-on delivery for Deloitte's banking and fintech clients. You'll serve as the technical point of contact for strategic accounts, leading discovery and design sessions, building POCs and demos, and facilitating workshops to help clients adopt cloud-native, event-driven, and AI-powered architectures.…See more You'll need deep Java/Spring Boot expertise, strong microservices and event-driven architecture knowledge (Kafka, CQRS, async patterns), hands-on multi-cloud experience (AWS primary, Azure/GCP secondary), and familiarity with LLM integration and agentic AI frameworks. The role demands you translate between technical stakeholders and executives, own the customer voice back to the product team, and travel 20–30% to client sites.

Build production AI features and workflows powered by large language models, including retrieval-augmented generation (RAG), agentic orchestration, and tool/function calling integrations. You will design and implement scalable microservices in Python or Java that connect foundation model APIs to business data and internal systems, with responsibility for AI quality, evaluation, observability, and safe deployment on AWS.…See more Collaborate with cross-functional teams to prototype solutions, measure outcomes, and move proven capabilities into production while maintaining reliability, security, and auditability.

Senior Machine Learning Engineer to design and ship production voice and conversational AI agents within AppFolio's Realm-X platform. You will architect real-time, multi-turn agent pipelines that balance reasoning depth against latency, lead a small pod of ML and platform engineers, and define quality metrics and evaluation harnesses.…See more Required expertise includes shipped production experience with agent frameworks (LangChain, LangGraph), voice stacks (STT/TTS/Voice-to-Voice models), LLM reasoning and tool use, Twilio, AWS, expert Python with async and WebSocket streaming, and demonstrated team leadership.

Senior Data Architect with 15+ years of experience designing and implementing enterprise data platforms that support modern AI/ML and Generative AI applications. Must have strong hands-on expertise in ETL/ELT, Python, SQL, and enterprise data warehousing, with production experience in Treasure Data, real-time analytics, streaming pipelines (Apache Kafka), and AI-ready data architectures including RAG, vector databases, and LLM integrations (LangChain, LangGraph, Azure OpenAI, AWS Bedrock).…See more Will design batch and real-time enterprise data architectures on cloud platforms (AWS, Azure, GCP, Snowflake, Databricks) with CDC/Debezium incremental processing capabilities.

Build and deploy production-ready AI solutions using LLM orchestration platforms (LangChain, LangGraph, CrewAI, n8n) and agentic workflows that integrate with existing data infrastructure like Snowflake. Develop sophisticated prompt engineering and RAG systems with vector databases, conduct independent data analysis to identify AI opportunities, and translate technical work into clear insights for leadership.…See more Move solutions from concept to deployed, maintainable tools with proper documentation and intuitive interfaces. Collaborate cross-functionally with data scientists, analysts, and stakeholders to drive organizational impact.

Staff Engineer or Architect role focused on building and orchestrating AI agents in a compliance-heavy, globally regulated environment. You will troubleshoot novel failures across models, tools, and infrastructure; set technical vision; and leverage LLMs, RAG, tool use, and agent frameworks (LangGraph, CrewAI, AutoGen) in production systems.…See more Requires 8+ years of software engineering experience, hands-on LLM and agent-framework work, end-to-end ownership, and demonstrated ability to use AI agents effectively in your own workflow while maintaining accountability and clear mental models of system behavior.

AppFolio is hiring a Staff Machine Learning Engineer to design, build, and operate their ML platform on AWS, supporting training, fine-tuning, inference, RAG, and cost optimization across the organization's AI initiatives. You'll partner with applied AI and research teams to productionize prototypes, maintain multi-provider LLM reliability (OpenAI, Google, Anthropic), and operate AI safety guardrails and authorization layers.…See more The role requires production-scale ML infrastructure experience on AWS (ECS, SageMaker, GPU fleets), deep knowledge of model serving and inference optimization, hands-on language model training, and demonstrated cost discipline across AI workloads.

Chief AI Subject Matter Expert leading the development of intelligent data processing pipelines, NLP systems, and AI-enabled dashboards for defense applications. The role requires 15+ years of experience with generative AI, LLMs, and agent-based development workflows, including hands-on use of tools like GitHub Copilot and Claude for code generation and automation.…See more Responsibilities include prototyping emerging AI tooling, mentoring engineering teams on AI integration, designing secure production AI solutions, and identifying opportunities to accelerate the software lifecycle through AI and automation. Must demonstrate expertise in LLM APIs, RAG architectures, vector databases, prompt engineering, and AI-specific security considerations in classified/sensitive environments.

Design and build AI agents and full-stack web applications that automate enterprise workflows, with expertise in agentic AI frameworks, LLM orchestration, and generative AI integration. Architect a multi-agent platform enabling PM and engineering agents to exchange plans and context, while developing backend services in C#/.NET/Python/TypeScript and modern Angular/React frontends that connect to enterprise systems like Jira, Microsoft 365, and SQL/NoSQL databases.…See more Define agentic engineering standards including tool contracts, prompt management, guardrails, and agent evaluation. Requires hands-on experience with LLM application development, RAG, tool calling, prompt engineering, agentic runtimes (LangGraph, AutoGen, n8n), and full-stack enterprise application development on AWS or Azure.

Design and build AI agents that automate workflows within a multi-agent platform, enabling PM and engineering agents to exchange plans and context over shared program data. Develop full-stack web applications with generative AI functionality—conversational interfaces, natural-language querying, automated summarization, and in-context recommendations—using C#, .NET, Python, TypeScript, Angular/React, and integrations with Jira, Microsoft 365, Confluence, and SQL/NoSQL stores.…See more Define agentic engineering standards including tool contracts, MCP servers, prompt management, memory, guardrails, human-in-the-loop approval, and evaluation harnesses. Requires hands-on experience with LLM application development, agentic runtimes like LangGraph or AutoGen, full-stack enterprise development, and cloud deployment on AWS or Azure.

This Technical Lead role focuses on architecting, developing, and deploying production-grade Agentic AI solutions on AWS using .NET/C#. The ideal candidate will have hands-on expertise in LLMs, generative AI, RAG, prompt engineering, and agent frameworks (LangChain, LangGraph, Semantic Kernel, AutoGen), combined with strong .NET enterprise development and AWS cloud-native skills.…See more Responsibilities include taking AI solutions from POC to production, designing microservices and REST APIs, and ensuring AI evaluation, monitoring, observability, and governance. Technical leadership, stakeholder management, and system design fundamentals are essential.

Build practical generative AI applications as a Python backend engineer, combining LLMs, RAG, and agentic AI systems. You'll develop FastAPI/Flask services, integrate LangChain/LangGraph workflows, manage vector databases, and deploy on AWS.…See more The role requires hands-on Python backend skills, prompt engineering, API design, and the ability to debug and own full-stack AI-powered services from development through testing and deployment.

This role combines software engineering leadership with lab automation integration and early-stage AI prototyping. You will own the translation layer between high-level workflow logic and low-level instrument control, deploy and maintain containerized services using Docker and Kubernetes with CI/CD practices, and build scalable Python applications connecting experimental readouts with downstream analysis tools.…See more You'll collaborate on incorporating AI-driven decision-making into automation workflows, mentor the automation engineering team, and help shape the technical roadmap for autonomous discovery systems.

This role leads enterprise generative AI architecture and solution delivery on Oracle Cloud Infrastructure, designing agentic workflows, RAG pipelines, and LLM-based integrations with Oracle applications. The candidate will define AI governance and security standards, identify high-value use cases, mentor technical teams, and guide model selection and optimization.…See more Requirements include 8+ years of enterprise architecture experience with 2+ years in AI/ML/GenAI solution architecture, hands-on expertise with OCI services (Generative AI Service, Functions, API Gateway, Data Science, Autonomous Database, Integration Cloud), and proficiency in Python, SQL, and REST APIs.

A Forward Deployed AI Engineer who builds and deploys production AI/ML and Generative AI applications, particularly agentic workflows and RAG systems integrated with enterprise data and business systems. The role requires 6+ years of software/ML/AI engineering experience, advanced Python proficiency, hands-on expertise with LLMs, modern GenAI frameworks (LangChain, LangGraph, LlamaIndex), and cloud platforms (Azure, AWS, GCP).…See more You'll own solutions from prototype through production, working directly with product and business stakeholders to identify where AI creates value, troubleshoot integration issues, and drive continuous improvement.

Senior Developer on Dell's Office of the CTO team responsible for developing new AI applications from concept to production. You'll work across the full stack in small cross-functional teams, rotating through projects involving generative AI, data engineering, and MLOps.…See more The role requires solid programming fundamentals, experience or strong interest in DevOps/XP practices (microservices, CI/CD, containerization), and proficiency in languages like Python, Go, Java, C++, or JavaScript.

Senior Developer role focused on developing new AI applications from concept to production within Dell's Office of the CTO. You'll work on small cross-functional teams using pair programming and agile methodologies, rotating through different projects and technologies across the full stack.…See more Required: strong programming fundamentals, proficiency in Go, Python, Java, JavaScript, C++, Bash, or similar languages, plus interest in DevOps practices (microservices, CI/CD, containerization), generative AI, and MLOps. Desired: 5+ years of software development experience, data engineering skills, and familiarity with GenAI frameworks like LangChain.

Build and test agent behavior for an AI-driven service, including test case design and evaluation checks distinct from traditional software testing. Support data ingestion pipelines using AWS and BigData tools (PySpark, Airflow), collaborate with product and senior engineers to ship features, and contribute to production support (monitoring, alerting, incident response).…See more Requires 1–2 years of software engineering experience, a Master's in Computer Science or related field, proficiency in Python or another backend language, SQL/NoSQL fundamentals, basic REST API design, and hands-on experience with at least one LLM project (tool calling, chaining, retrieval, or multi-step coordination). Self-directed learner excited about AI tooling and focused on shipping end-to-end products.

Lead machine learning strategy and development for AppFolio's Leasing products, owning the ML roadmap and autonomous leasing agent architecture. Build evaluation frameworks, model quality infrastructure, and establish ML standards across the Leasing Engineering team while ensuring production-grade reliability, SLOs, and observability.…See more Translate research into shipped features by evaluating fine-tuning approaches, RAG patterns, and agentic systems; operate with production discipline on a SaaS platform serving real customer workflows.

Senior AI Subject Matter Expert responsible for developing intelligent data processing and NLP pipelines, AI-enabled dashboards, and proofs-of-concept for AI use cases. The role requires 7+ years of professional experience with advanced expertise in LLM APIs, RAG architectures, agent-based development, generative AI coding tools, and secure AI deployment patterns.…See more Responsibilities include prototyping emerging AI developer tooling, mentoring engineering teams on generative AI workflows, and identifying software lifecycle areas that can be accelerated through AI and automation. The candidate must critically evaluate AI-generated code for correctness and security, understand AI-specific security risks across the full SDLC, and scope requirements for engineering solutions that meet business challenges with measurable outcomes.

AI Architect role requires designing and delivering enterprise-scale AI/ML solutions on AWS, with 5–7 years of cloud experience and 2–3 years hands-on with LLMs, agentic frameworks, and AI/ML services. The position demands deep expertise in AWS AI services (Bedrock, SageMaker, Kendra), orchestration frameworks (LangChain, LangGraph), RAG pipelines, MLOps tooling, and responsible AI principles.…See more Candidates must architect scalable, cost-optimized solutions integrating AI with cloud infrastructure, data platforms, and microservices, and communicate complex technical concepts to executive and technical audiences.

Own and evolve the software translation layer between high-level workflow logic and low-level laboratory instrument control, integrating liquid handlers, plate readers, robotic workstations, and analytical instruments. Deploy and maintain containerized services using Docker, Kubernetes, GitOps, and CI/CD practices, building scalable Python applications and data pipelines that connect experimental readouts with LIMS and downstream analysis tools.…See more Collaborate with the team to prototype AI-driven decision-making and autonomous orchestration in lab workflows, evaluating LLM tooling and agent frameworks for practical applicability. Serve as a technical authority and mentor, influencing the broader technical roadmap for autonomous discovery systems and helping grow the automation engineering team's capability.

Lead the design, development, and deployment of enterprise-scale Generative AI and LLM solutions across Azure and AWS environments. Define AI architecture frameworks, standards, and governance practices while architecting RAG systems, agentic AI, multi-agent systems, and vector database solutions.…See more Partner with business leaders and engineering teams to translate business requirements into scalable, secure, and responsible AI platforms. Mentor architects and data science teams while evaluating emerging AI technologies and driving innovation initiatives.