Staff II Software Engineer AI/ML Ops

Responsibilities

• Lead data pipeline development: Build and maintain PySpark ETL pipelines with high data quality and performance
• Manage integrations: Establish robust connections to client data sources via APIs and tools like FiveTran, Plaid, and BlackLine’s own internal connector ecosystem
• Ensure reliability: Monitor pipeline performance, automate testing, and validate data accuracy
• Optimize for scale: Implement performance improvements (e.g., CDC mechanisms, indexing strategies) for large-scale datasets
• Collaborate & innovate: Work with business stakeholders to refine data requirements and integrate cutting-edge AI and big data technologies

Qualifications

• Knowledge: Extensive practical experience with consistent, demonstrated success developing effective business solutions/applications for products or services that may effect broad areas of the org
• Technical Skills: Strong programming skills in languages such as Python, Java, or Scala
• Expertise in ML frameworks (TensorFlow, PyTorch, scikit-learn) and orchestration tools (Airflow, Kubeflow, Vertex AI, MLflow)
• Proven experience operating production pipelines for ML and LLM-based systems across cloud ecosystems (GCP, AWS, Azure)
• Deep familiarity with LangChain, LangGraph, ADK or similar agentic system runtime management
• Strong competencies in CI/CD, IaC, and DevSecOps pipelines integrating testing, compliance, and deployment automation
• Hands-on with observability stacks (Prometheus, Grafana, Newrelic) for model and agent performance tracking
• Understanding of governance frameworks for Responsible AI, auditability, and cost metering across training and inference workloads
• Proficiency in containerization technologies (e.g., Docker, Kubernetes)
• Operations and Infrastructure: Proficient in scripting languages (e.g., Bash, python) for automation
• Experience with workflow orchestration tools (e.g., Apache Airflow)
• Expertise in managing and optimizing cloud-based infrastructure
• Familiarity with DevOps practices and tools for automated deployment
• Understanding of network configurations and security protocols
• Problem-solving and Critical Thinking: Ability to define problems, collect and analyze data, and propose innovative solutions
• Strong critical thinking skills to evaluate models, identify limitations, and adaptability and Learning Agility: Comfortable working in a fast-paced, rapidly evolving environment

What You'll Bring

• Education and Experience: Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or a related field
• Skills: Strong programming skills in languages such as Python, Java, or Scala
• Expertise in ML frameworks (TensorFlow, PyTorch, scikit-learn) and orchestration tools (Airflow, Kubeflow, Vertex AI, MLflow)
• Proven experience operating production pipelines for ML and LLM-based systems across cloud ecosystems (GCP, AWS, Azure)
• Deep familiarity with LangChain, LangGraph, ADK or similar agentic system runtime management
• Strong competencies in CI/CD, IaC, and DevSecOps pipelines integrating testing, compliance, and deployment automation
• Hands-on with observability stacks (Prometheus, Grafana, Newrelic) for model and agent performance tracking
• Understanding of governance frameworks for Responsible AI, auditability, and cost metering across training and inference workloads
• Proficiency in containerization technologies (e.g., Docker, Kubernetes)
• Operations and Infrastructure: Proficient in scripting languages (e.g., Bash, python) for automation
• Experience with workflow orchestration tools (e.g., Apache Airflow)
• Expertise in managing and optimizing cloud-based infrastructure
• Familiarity with DevOps practices and tools for automated deployment
• Understanding of network configurations and security protocols
• Problem-solving and Critical Thinking: Ability to define problems, collect and analyze data, and propose innovative solutions
• Strong critical thinking skills to evaluate models, identify limitations, and adaptability and Learning Agility: Comfortable working in a fast-paced, rapidly evolving environment