knowledge-graphs jobs in San Diego

Mid-level software engineer building AI/ML capabilities for a defense customer. You'll develop NLP and machine learning pipelines in Python (text analytics, topic modeling, embeddings, entity extraction), design knowledge graphs and network-analysis tools, develop collaborative TypeScript front-end applications, and deploy APIs and production systems.…See more Requires 4+ years Python development or equivalent front-end experience plus 2 years Python, hands-on NLP/ML experience, and ability to work with limited supervision.

This Staff AI Engineer role focuses on architecting and implementing secure, scalable frameworks for autonomous AI agents at enterprise scale. The engineer will lead the technical roadmap for agent management—from provisioning and orchestration to compliance and retirement—while ensuring AI agents are secure by design with built-in visibility and guardrails.…See more The role requires 8+ years of software architecture and backend systems experience, deep knowledge of autonomous agent frameworks (LangChain, AutoGen, CrewAI), and expertise in cloud infrastructure (AWS, Azure, GCP) and Kubernetes. You'll collaborate cross-functionally with researchers, platform engineers, and product teams to bring agentic AI capabilities to production while establishing best practices for agent safety, observability, and ethical deployment.

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.

Staff Data Engineer role at Credit Karma building petabyte-scale data infrastructure and streaming platforms on GCP. You will design and operate Kafka-based streaming infrastructure, build cloud-native data pipelines using Dataflow/Beam, Flink, and Spark, and create persistence frameworks across Spanner, MySQL, and BigQuery.…See more The role requires 7+ years backend/data systems experience in JVM languages (Scala/Java), expertise with high-throughput distributed systems, and deep knowledge of streaming platforms, Apache Beam, CDC patterns, encryption, and data governance frameworks. You'll also integrate AI/ML and generative AI technologies including LLMs, RAG, semantic search, and knowledge graphs into the data platform.

Principal Engineer leading the technical direction for ServiceNow's Conversational Analytics platform, which enables customers to query data in natural language using AI. The role combines hands-on architecture and prototyping with mentorship of engineering teams, requiring deep expertise in AI/ML systems, vector retrieval, agentic architectures, and knowledge graphs.…See more You'll collaborate with product and leadership to design cloud-based solutions integrating LLMs and AI into enterprise workflows, with accountability for customer success metrics and evaluation frameworks.

Design, build, and ship LLM-powered capabilities end to end—from prototyping and fine-tuning models to deploying production agents and retrieval systems. Own the full stack: prompt and context engineering, multi-step agent design with tool calling, RAG systems (embeddings, chunking, hybrid search, reranking), fine-tuning on multi-GPU with LoRA/QLoRA, evaluation and tracing infrastructure, and clean APIs for other engineers.…See more Work in a secure, distributed environment where the platform runs on customer compute, cloud, or hybrid setups, requiring expertise with both commercial and self-hosted models.

As Principal Software Engineer for AI & Data Platform, you will architect the data foundation for scientific and engineering R&D platforms, designing scalable data processing patterns, ML training pipelines, and intelligent workflow interfaces. You will own end-to-end responsibilities including data modeling for multi-use analytics and ML, building production training and fine-tuning pipelines, model evaluation and benchmarking, and setting engineering standards for the team.…See more The role requires 10+ years shipping production software, expert-level Python, deep experience with large-scale data systems (object storage, analytical processing, training formats), hands-on ML pipeline development, and the ability to set technical direction in early-stage environments while implementing it yourself.