Anvilogic is a Palo Alto-based AI cybersecurity startup founded in 2019 by security veterans and data scientists from Fortune 500 companies.
Our mission is to democratize threat detection and hunting for today’s SOC teams to easily be done across hybrid, multi-clouds and security data lakes without needing to centralize data or rip and replace tools. Further, with our investments in AI-powered automation of detection-as-code to create, test, tune and deploy detections, SOC users can implement high-efficacy detection and hunting techniques without writing a single line of code nor manually wrangling data.
Anvilogic raised $45M Series C funding in April 2024 and is backed by top-tier VC firms and prominent industry executives. Anvilogic’s AI-powered Multi-Data Platform SIEM is used by many of the industry’s most advanced security teams.
Learn about our customers: anvilogic.com/customers
JOB DESCRIPTION
As a Senior Software Engineer, Data at Anvilogic, you are responsible for designing, building, and operating our high scale data ingestion pipelines. You will work directly on company critical projects related to how our users’ data is brought into our data stores, normalized across different data stores, and exposed for analysis, using technologies such as AWS, Azure, Snowflake, Databricks, and Splunk.
- Design, build, and operate data ingestion and normalization pipelines
- Work with product management teams to map out non-functional requirements and implement those requirements in your services
- Deploy and monitor resources in cloud and data lake providers
- Spread knowledge of data pipeline best practices throughout Anvilogic through mentorship, documentation, and brown bag sessions
Requirements
Minimum Qualifications
- 4+ years of software development experience
- Excellent written and verbal communication skills
- Experience with data lakes such as Snowflake or Databricks
- Experience with cloud providers such as AWS, GCP, or Azure
- Experience with defining non-functional requirements, measuring SLOs, and balancing tech foundation and product timelines
- Ability to quickly come up to speed on our data pipeline techstack, which uses Python deployed on Snowflake and Databricks via AWS, Azure, and GCP.
Preferred Qualifications
- Experience with ingesting large amounts of user data into Snowflake or Databricks
- Experience deploying services using infrastructure-as-code (Terraform, AWS SAM, CloudFormation, or CDK).
- Experience with observability technologies like Grafana and Sentry
- Some experience with LLMs, implementing standard patterns (Agents, RAG, Tools), and leveraging popular frameworks.
- Familiarity with security data (e.g., endpoint and network logs)
Benefits
- US Salary Transparency: The base salary range for this full time position is $160,000-$190,000 + equity + benefits. Final compensation will depend on experience, qualifications, and location.
- Competitive salary with equity in the company
- Comprehensive medical, dental, and vision insurance
- Unlimited paid time off policy for work life balance
- 401(k) retirement plan with company match
- Monthly stipend for home internet and cell phone expenses
Top Skills
What We Do
No more legacy SIEM. Time for a Modern approach. Democratize security across your hybrid, multi-cloud, and other data lakes.
Anvilogic is an AI-Driven SOC platform for threat detection and incident response that helps to unify and automate security operations across people, processes, and technology enabling security teams to reduce the time, manual effort, complexity, and expertise needed for building detections and managing your overall security operations – through AI-driven recommendations and frameworks gain visibility into complex interactions across different systems and correlate seemingly unrelated events. Gain the ability to continuously assess, prioritize, detect, hunt, and triage to quickly mitigate risk.
Anvilogic was built by security practitioners for security practitioners and empowers security professionals at every level to take control of the backlog chaos, eliminate silos, and simplify complexities so they can focus on what matters.
