dagster jobs in San Diego

Build and ship agentic AI capabilities (e.g., Vertex AI-based Discovery Agents) from design through production, owning the full software development lifecycle, implementation, testing, and deployment. Harden proof-of-concept agent code into production-grade quality with strong error handling, observability, and testing.…See more Design test cases and evaluation checks for non-deterministic agent behavior, and build data ingestion pipelines using AWS and big-data tooling. Contribute to production support including monitoring, alerting, and incident response for an AI-driven service.

Staff Engineer who will design, build, and operate the Forge Platform—a distributed-systems foundation serving autonomy, ML Ops, simulation, and application teams. You will own architecture and technical standards for workflow orchestration, asynchronous processing, event-driven systems, and long-running service workflows while remaining hands-on in implementation, production troubleshooting, and reliability improvement.…See more Required: strong production experience with distributed systems, cloud-native platforms, or backend infrastructure; fluency in Go and Python; deep understanding of failure handling, consistency, fault tolerance, and state management; and ability to turn recurring infrastructure needs into reusable platform capabilities. You will work across Kubernetes, service networking, observability, and data pipelines to enable downstream teams to move faster on mission-critical systems.

Staff Engineer responsible for designing, building, and operating the Forge Platform—a distributed-systems foundation serving autonomy, ML, simulation, and test teams. You will architect cloud-native backend infrastructure, establish reusable platform capabilities, define technical standards, and remain hands-on in production troubleshooting, performance analysis, and reliability improvement.…See more Required: deep expertise in production distributed systems, Go and Python, workflow orchestration, and the ability to translate complex architecture into usable interfaces across multiple downstream teams.

Principal Data Platform Engineer responsible for designing and implementing cloud-native data integrations using AWS services (S3, Glue, Lambda) and Snowflake. Builds and maintains data transformation models using dbt, manages Snowflake platform infrastructure, and leads cross-functional collaboration between engineering, analytics, and business teams.…See more Requires 8+ years in data engineering or data platform roles with expert-level Python, SQL, dimensional modeling, and infrastructure-as-code expertise. Acts as a technical mentor and translates business requirements into data architecture priorities.

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.

Build and operate the data and ML infrastructure powering an AI platform for materials science, owning both sides: data pipelines that ingest and curate large-scale scientific output into training-ready formats, and model packaging, serving, monitoring, and CI/CD systems that move models safely from research to production across customer environments. You will design data ingestion and transformation workflows, implement validation and quality gates, package and version models with reproducible builds, run models through batch and online inference with safe rollout and rollback, monitor for drift and degradation, and build observability and internal tooling for engineering and science teams.…See more The role requires 6+ years shipping production software with deep expertise in data systems, ML infrastructure, containers, orchestration, and observability.

Design, build, and scale ETL/ELT pipelines and cloud data warehouse infrastructure using Python, SQL, and modern orchestration tools like Apache Airflow or Prefect. Own the end-to-end data infrastructure that powers business intelligence and operational reporting, including data quality checks, anomaly detection, and performance optimization.…See more Collaborate with analytics and software engineering teams to define data modeling standards and maintain infrastructure-as-code deployments using Terraform and CI/CD. Requires 3–6 years of data engineering or backend development experience with advanced SQL, Python, and hands-on work with cloud data warehouses like Snowflake or BigQuery.