Software Engineer AI/ML Ops

Software Engineer AI/ML OpsThis is a full-time, hybrid opportunity based in Pleasanton, California with a leading enterprise SaaS organization building next-generation AI-driven accounting solutions.

The role focuses on AI/ML Ops, leveraging technologies like PySpark, Python, cloud platforms (AWS/GCP/Azure), and modern orchestration tools to build scalable data pipelines and production-grade machine learning systems. This opportunity is ideal for engineers who want to work at the intersection of data engineering, machine learning, and infrastructure. The standout feature of this role is ownership of end-to-end AI data pipelines powering agentic AI systems at scale. The team is looking for someone who thrives in fast-paced environments, enjoys working with cutting-edge AI tooling, and wants to deepen expertise in ML systems, observability, and cloud-native infrastructure. You will gain hands-on experience with large-scale data systems, LLM-based pipelines, and advanced AI orchestration, all while collaborating in a culture that values continuous learning and innovation.Required Skills & Experience2+ years of experience in software engineering with Python, Java, or ScalaHands-on experience building and maintaining data pipelines (ETL/ELT), preferably with PySparkExperience with machine learning frameworks such as TensorFlow, PyTorch, or scikit-learnExperience deploying and managing ML/LLM pipelines in production environmentsFamiliarity with orchestration tools such as Airflow, Kubeflow, MLflow, or Vertex AIUnderstanding of distributed systems and large-scale data processingExperience with CI/CD pipelines, infrastructure-as-code, and DevSecOps practicesKnowledge of observability tools such as Prometheus, Grafana, or New RelicExperience with Docker and Kubernetes for containerization and scalingDesired Skills & ExperienceExperience integrating with data platforms such as Fivetran, Plaid, or similar API-based connectorsFamiliarity with LangChain, LangGraph, or other agentic AI frameworksExperience optimizing large-scale data pipelines (CDC, indexing, performance tuning)Knowledge of Responsible AI practices including governance, auditability, and cost trackingStrong scripting and automation skills (Python, Bash)Experience working with cloud-native infrastructure across AWS, GCP, or AzureFamiliarity with networking, security practices, and system reliabilityStrong analytical and problem-solving skills with a focus on data-driven decision makingTech Breakdown40% Data Engineering (PySpark, ETL pipelines, data integration)30% AI/ML Systems (LLM pipelines, model orchestration, agent frameworks)20% Cloud & Infrastructure (AWS/GCP/Azure, Kubernetes, CI/CD)10% Observability & Optimization (monitoring, tuning, reliability improvements)Daily Responsibilities75% Hands On Engineering (pipeline development, ML systems, infrastructure)5% Management Duties20% Team Collaboration (cross-functional work with engineering and business stakeholders)The OfferYou will receive the following benefits:Medical, Dental, and Vision InsuranceVacation TimeStock OptionsApplicants must be currently authorized to work in the US on a full-time basis now and in the future.