vertex-ai jobs in San Diego

Staff Engineer responsible for designing and building scalable test automation frameworks and CI/CD infrastructure for machine-learning systems at scale. The role requires expertise validating ML quality across the full lifecycle (data, training, evaluation, packaging, deployment, monitoring), GPU-accelerated workloads in Kubernetes, and integrated hardware-software systems.…See more You will develop automated evaluation suites, performance baselines, release thresholds, and observability solutions while mentoring teams on ML testing best practices and dependency/reproducibility standards.

Staff Engineer responsible for designing and implementing scalable test automation frameworks and infrastructure for machine learning systems across multiple engineering teams. The role requires expertise in validating ML pipelines across data, training, evaluation, deployment, and monitoring; testing GPU-accelerated workloads in Kubernetes; qualifying integrated hardware and software systems; and developing comprehensive integration and regression strategies.…See more Deep experience with Python automation, distributed systems testing, performance profiling, and observability is essential, along with strong system-design skills for complex, multi-tenant environments.

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.

As a Forward Deployed Engineer IV in Applied AI at Google Cloud, you will lead end-to-end engineering for production conversational AI systems, transforming prototypes into scalable agentic workflows deployed at customer sites. You'll architect multi-agent systems using frameworks like ReAct, optimize RAG implementations, debug agent logic across microservices, and connect AI systems to enterprise infrastructure.…See more The role requires 8+ years of software development (Python or similar), experience with infrastructure-as-code (Terraform), cloud platform deployment (GCP), and hands-on full-stack application development. You'll travel up to 50% and work directly with customers to establish production AI journeys while identifying patterns that feed back into product improvements.

Lead the design, governance, and technical implementation of an enterprise API and AI gateway platform serving internal and external consumers. Define solution standards, security controls, compliance protocols aligned to financial services regulations, and LLM integration patterns across Apigee X, MCP servers, and multiple AI providers.…See more Manage a team through API modernization and AI gateway buildout while actively contributing hands-on engineering on proxies, policies, and MCP integrations when needed.

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.

Lead the design and delivery of enterprise AI platforms and applications on Google Cloud, leveraging Vertex AI, Gemini, and cloud-native technologies. Design, fine-tune, and govern LLM solutions; build RAG and agentic systems; and define end-to-end architectures spanning data pipelines, feature engineering, model lifecycle, APIs, and MLOps/LLMOps.…See more Architect cloud-native applications on GKE, Cloud Run, and managed services while implementing security, governance, and production-grade monitoring for AI/ML systems at scale.