About the role
Please note, this team is hiring across all levels and candidates are individually assessed and appropriately leveled based upon their skills and experience.
The Data Agentic AI team is building the next-generation Agentic AI and conversational system, a pivotal solution designed to elevate Netskope's user experience and the overall security of customer data and networks. By leveraging underlying systems and data capabilities, this system will significantly enhance network security, substantially reducing the operational overhead for customers in maintaining a secure posture. This solution is central to the company's next phase of offerings.
We seek experienced, hands-on engineers to develop optimised Multi-Agent workflows for data products. This impactful role involves collaborating with engineering and product teams to build highly scalable systems that address real-world security challenges. The resulting solutions must be accurate, provide high confidence to customers, and integrate seamlessly across various Netskope products.
What's in it for you
You will be part of the team that brings together the power of an Agentic System to network and data security solutions
You will be part of a growing team of renowned industry experts in the exciting space of Network and Data security
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
Drive innovation by integrating the latest AI/ML techniques into security products and services.
Drive the end-to-end development and deployment of Agentic assistant, powered by cutting-edge Multi-Agent Workflows.
Implement comprehensive evaluation and observability strategies for the Agentic AI Solutions
Architect and implement scalable data pipelines for processing large-scale datasets from logs, network traffic, and cloud environments.
Apply MLOps & LLMOps best practices to deploy and monitor machine learning models & agentic workflows in production.
Lead the design, development, and deployment of AI/ML models for threat detection, anomaly detection, and predictive analytics in cloud and network security.
Collaborate with cloud architects and security analysts to develop cloud-native security solutions x platforms like AWS, Azure, or GCP.
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.
Required skills and experience
Software Engineering
8-12 years of software engineering experience with demonstrated progression to senior roles.
Expertise in Python with experience in one other language (C++/Java/Go) for data and ML solution development.
Expertise in scalable system design and performance optimization for high-throughput applications.
Experience of building & consuming MCP clients & servers.
Experience with asynchronous programming, including web-sockets, FastAPI, and Sanic.
Experience in system cost optimization
AI/ML Expertise
Experience with working with LLM and Agentic systems
Expertise in prompt engineering patterns such as chain of thought, ReAct, zeroshot and fewshot.
Experience in Langgraph/Autogen/AWS Bedrock/Pydantic AI/Crew AI
Strong understanding of MLOps practices and tools (e.g., Sagemaker/MLflow/ Kubeflow/Airflow/Dagster).
Experience with evaluation & observability tools like Langfuse/Arize Phoenix/ Langsmith.
Proficiency in working with vector databases such as PGVector, Pinecone, and Weaviate.
Good-to-Have Skills and Experience
AI/ML Expertise
Has built & deployed a multi-agent or agentic RAG workflow in production.
Proficiency in advanced machine learning techniques, including neural networks (e.g., CNNs, Transformers) and anomaly detection.
Experience with AI frameworks like Pytorch, TensorFlow and Scikit-learn.
Data Engineering
Expertise designing and optimizing ETL/ELT pipelines for large-scale data processing.
Proficiency in working with relational and non-relational databases, including ClickHouse and BigQuery.
Experience with cloud-native data tools like AWS Glue, BigQuery, or Snowflake.
Graph database knowledge is a plus.
Cloud and Security Knowledge
Understanding of cloud platforms (AWS, Azure, GCP) and their services.
Experience with network security concepts, extended detection and response, and threat modeling.
Education
BSCS or equivalent required, MSCS or equivalent strongly preferred
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