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# Backend Software Engineer

- **Company:** · Sentinelone
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $132,000.0 - $182,000.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Databases, Customer Data Management, Information Engineering, DevOps, Distributed Systems, Internet Security, Machine Learning, NoSQL, Performance Tuning, Tensorflow, Prometheus, Software Engineering, SQL Databases, Parquet, Datadog, Data Processing, Google Cloud, Pytorch, Large Language Models, Grafana, Apache Spark, Deep Learning, Reliability of Systems, Backend, Kubernetes, Apache Flink, Apache Kafka, Data Management, Machine Learning Operations, Terraform, Splunk, SentinelOne Expertise, Data Pipelines, Elk Stack, Microservices
- **Published:** August 1, 2026
- **Apply:** https://www.careerbuilder.com/job-details/senior-backend-software-engineer-observoai--9b8e4bf6-b3a6-4496-865e-ed43da59525b

## About the Role

* 5+ years of software engineering experience focused on distributed systems, data engineering, or ML infrastructure with expert-level proficiency in Go, Rust, or Java.
 * Extensive experience with cloud platforms (AWS, GCP, Azure), container orchestration (Kubernetes), and a proven track record leading and scaling data pipelines using Kafka, Spark, or Flink.
 * Deep expertise in database technologies (SQL and NoSQL) and advanced experience with machine learning frameworks (TensorFlow, PyTorch) and MLOps practices for production ML systems.
 * Expert knowledge of observability tools and standards, including Prometheus, Grafana, ELK stack, OpenTelemetry, and Parquet, alongside extensive experience with Infrastructure as Code (Terraform).
 * Strong leadership and technical communication skills, with a track record of mentoring engineers, planning technical strategy, and driving decisions across multiple teams and stakeholders., Amazon Web Services (AWS), Application Programming Interface (API), Architectural Services, Artificial Intelligence (AI), Automation, Best Practices, Cancer, Cellular Telephone, Cloud Computing, Coaching, Communication Skills, Cost Control, Cross-Functional, Customer/Client Research, Data Management, Data Processing, Data Science, Database Technology, DevOps, Distributed Computing, Editing, Employee Assistance Plan, Endpoint Security, Engineering, Flexible Spending Accounts, GCP (Good Clinical Practices), Health Insurance, Insurance, International Business, Internet Security, Java, Leadership, Legal, Machine Learning, Mentoring, Metrics, Microservices, Microsoft Windows Azure, NoSQL, Performance Tuning/Optimization, Problem Solving Skills, Process Capability, Process Improvement, Production Systems, Reimbursement, Rust Programming Language, SQL (Structured Query Language), Software Engineering, Splunk, Stock Purchase Plans, Strategic Planning, Systems Reliability, Technical Leadership,
Technical Strategy, Technical/Engineering Design, Telemetry, Willing to Travel

## Description

* Lead the architectural design and technical roadmap for scalable, high-performance data processing pipelines capable of handling petabyte-scale telemetry data (logs, metrics, traces).
 * Drive the development and optimization of ML-driven data routing and transformation engines to reduce customer data volumes by 80%+ while architecting real-time analytics systems using advanced machine learning and LLMs.
 * Design cloud-native microservices and APIs that integrate seamlessly with major observability platforms (Splunk, Elastic, Datadog) while establishing robust monitoring, alerting, and observability solutions.
 * Lead cross-functional technical initiatives and decision-making forums, collaborating with Product, Data Science, and DevOps teams to translate strategic vision into technical solutions and company-wide standards.
 * Provide technical leadership and mentorship to senior and junior engineers, driving system performance and reliability optimization while establishing engineering best practices and culture.


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