Staff Engineer, Data Engineering

What you will be doing

• Lead the design, development, and deployment of  AI / ML models  for threat detection, anomaly detection, and predictive analytics in cloud and network security.
• Architect and implement  scalable data pipelines  for processing large-scale datasets from logs, network traffic, and cloud environments.
• Apply  MLOps best practices  to deploy and monitor machine learning models in production.
• Collaborate with cloud architects and security analysts to develop cloud-native security solutions leveraging platforms like AWS, Azure, or GCP.
• Build and optimize  Retrieval-Augmented Generation (RAG) systems  by integrating large language models (LLMs) with vector databases for real-time, context-aware applications.
• Analyze network traffic, log data, and other telemetry to identify and mitigate cybersecurity threats.
• Ensure data quality, integrity, and compliance with GDPR, HIPAA, or SOC 2 standards.
• Drive innovation by integrating the latest AI / ML techniques into security products and services.
• Mentor junior engineers and provide technical leadership across projects.

Required skills and experience

AI / ML Expertise

• Proficiency in advanced machine learning techniques, including neural networks (eg, CNNs, Transformers) and anomaly detection.
• Experience with AI frameworks like  TensorFlow, PyTorch, and Scikit-learn  .
• Strong understanding of MLOps practices and tools (eg, MLflow, Kubeflow).
• Experience building and deploying Retrieval-Augmented Generation (RAG) systems, including integration with LLMs and vector databases.

Data Engineering

• Expertise designing and optimizing  ETL / ELT pipelines  for large-scale data processing.
• Hands-on experience with big data technologies (eg, Apache Spark, Kafka, Flink).
• Proficiency in working with relational and non-relational databases, including  ClickHouse  and  BigQuery  .
• Familiarity with vector databases such as  Pinecone  and  PGVector  and their application in RAG systems.
• Experience with cloud-native data tools like AWS Glue, BigQuery, or Snowflake.

Cloud and Security Knowledge

• Strong understanding of cloud platforms  (AWS, Azure, GCP  ) and their services.
• Experience with network security concepts, extended detection and response, and threat modeling.

Software Engineering

• Proficiency in  Python, Java, or Scala  for data and ML solution development.
• Expertise in scalable system design and performance optimization for high-throughput applications.

Leadership and Collaboration

• Proven ability to lead cross-functional teams and mentor engineers.
• Strong communication skills to present complex technical concepts to stakeholders.

Education

• BSCS or equivalent required, MSCS or equivalent strongly preferred

Skills Required

Java, MLops, Hippa, Azure, Python, Aws, Oltp