About the Role

We are seeking an exceptional Senior Staff Software Engineer to build next-generation security analytics and AI-powered capabilities within Netskopes platform. This is a high-impact individual contributor role for an engineer who excels at solving complex technical problems at the intersection of artificial intelligence large-scale data systems and cybersecurity.

As a Senior Staff Engineer you will design and implement sophisticated systems that leverage cutting-edge AI/ML techniques graph-based analytics and real-time data processing to solve critical security challenges. You will work on problems spanning threat detection risk assessment behavioral analytics and intelligent automationbuilding the systems that help security teams at the worlds largest enterprises detect and respond to threats.

This role requires deep technical expertise with strong hands-on implementation skills. You will collaborate closely with Distinguished Engineers senior engineers product managers and security researchers to deliver production-quality solutions that operate at massive scale. Your code and architectural decisions will directly impact how thousands of organizations protect their critical assets.

Required Skills and Experience

Strong Technical Foundation

• 10-15 years of software engineering experience with progression to senior roles
• Expert-level proficiency in Python with modern frameworks and libraries
• Production experience with at least one other language (Go Java Scala or C)
• Deep understanding of distributed systems including consistency scalability and fault tolerance
• Strong computer science fundamentals: algorithms data structures complexity analysis
• Expert-level proficiency in Python with modern frameworks and libraries
• Experience with cloud platforms (AWS Azure or GCP) and cloud-native architectures
• Solid understanding of software design patterns and system architecture principles

AI/ML & Advanced Analytics Expertise

• 3 years hands-on experience building AI/ML systems in production including:
• Working with Large Language Models (OpenAI API Anthropic Claude or similar)
• Building RAG systems using frameworks like LangChain or LangGraph
• Implementing vector search with vector databases (Pinecone Weaviate Chroma pgvector)
• ML model training evaluation and deployment
• MLOps practices including model monitoring and versioning
• Experience with graph databases (Neo4j TigerGraph or similar) including:
• Graph data modeling and schema design
• Writing complex graph queries (Cypher Gremlin or similar)
• Graph algorithms and traversals
• Strong data engineering skills:
• Streaming data processing (Kafka Flink or similar)
• Large-scale data storage systems (ClickHouse Snowflake BigQuery)
• ETL/ELT pipeline design and implementation
• Working with both structured and unstructured data

Cybersecurity Domain Knowledge

• 5 years of experience in cybersecurity with practical understanding of:
• Security operations workflows
• Threat detection and incident response
• Security data sources (logs network traffic endpoint telemetry)
• Common attack patterns and TTPs
• Security frameworks (MITRE ATT&CK)
• Experience with security analytics systems such as:
• Behavioral analytics and anomaly detection
• Threat intelligence platforms
• Security automation and orchestration
• Familiarity with security compliance requirements (SOC 2 GDPR HIPAA)

Technical Execution Skills

• Proven track record delivering complex projects from design through production deployment
• Strong debugging and troubleshooting skills for distributed systems
• Experience with testing including unit testing integration testing and test automation
• Proficiency with version control (Git) and CI/CD pipelines
• Understanding of monitoring and observability (Prometheus Grafana distributed tracing)
• Experience with containerization (Docker Kubernetes)
• Ability to work with ambiguity and drive technical decisions with incomplete information
• Strong problem-solving skills breaking down complex problems into manageable components

Communication & Collaboration

• Excellent written communication for technical documentation and design specs
• Clear verbal communication for explaining complex technical concepts
• Collaborative mindset working effectively with cross-functional teams
• Ability to give and receive constructive feedback in code reviews and design discussions
• Experience mentoring junior and mid-level engineers
• Customer empathy understanding security practitioner needs and workflows

Preferred Qualifications

• Experience in cybersecurity product companies or security-focused roles
• Background in security research or threat hunting
• Contributions to open-source projects in AI/ML security or data engineering
• Experience with advanced graph algorithms: community detection centrality measures path finding
• Familiarity with behavioral analytics and UEBA systems
• Knowledge of prompt engineering and LLM optimization techniques
• Experience with real-time systems requiring low-latency processing
• Understanding of data privacy and secure system design
• Experience with streaming ML and online learning systems
• Conference presentations or blog posts on technical topics

Technical Environment

You will work hands-on with:

• Languages: Python (primary) Go Java/Scala
• AI/ML Frameworks: TensorFlow PyTorch scikit-learn LangChain LangGraph
• LLM APIs: OpenAI Anthropic Claude Azure OpenAI
• Graph Databases: Neo4j TigerGraph or Apache AGE
• Vector Databases: Pinecone Weaviate Chroma pgvector
• Streaming: Apache Kafka Apache Flink
• Data Storage: ClickHouse PostgreSQL data lakes (S3/Delta/Iceberg)
• Cloud: AWS Azure or GCP
• Orchestration: Kubernetes Docker Airflow
• Monitoring: Prometheus Grafana ELK stack
• Development: Git CI/CD (Jenkins GitLab GitHub Actions)

What We Offer

• Cutting-edge technical challenges at the intersection of AI and cybersecurity
• Hands-on work with latest technologies (LLMs graph databases vector search streaming)
• Collaborate with world-class engineers and security experts
• Competitive compensation including base salary equity and comprehensive benefits
• Flexible work arrangements (remote or hybrid options)
• Professional development budget for conferences courses and certifications
• Learning opportunities staying current with rapidly evolving AI/ML landscape
• Work-life balance with flexible schedules and unlimited PTO
• Impact at scale solving real security problems for global enterprises
• Modern tech stack and freedom to influence tooling decisions

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