What's in it for you

You will be part of a growing team of renowned industry experts in the exciting space of Data and Cloud Analytics

Your contributions will have a major impact on our global customer-base and across the industry through our market-leading products

You will solve complex, interesting challenges, and improve the depth and breadth of your technical and business skills.

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 (e.g., CNNs, Transformers) and anomaly detection.
• Experience with AI frameworks like TensorFlow, PyTorch, and Scikit-learn.
• Strong understanding of MLOps practices and tools (e.g., 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 (e.g., 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