Senior Backend Engineer (Cloud Services & Machine Learning Deployment)

About Zscaler

Zscaler (NASDAQ: ZS) accelerates digital transformation so that customers can be more agile, efficient, resilient, and secure. The Zscaler Zero Trust Exchange is the company’s cloud-native platform that protects thousands of customers from cyberattacks and data loss by securely connecting users, devices, and applications in any location.

With more than 10 years of experience developing, operating, and scaling the cloud, Zscaler serves thousands of enterprise customers around the world, including 450 of the Forbes Global 2000 organizations. In addition to protecting customers from damaging threats, such as ransomware and data exfiltration, it helps them slash costs, reduce complexity, and improve the user experience by eliminating stacks of latency-creating gateway appliances.

Zscaler was founded in 2007 with a mission to make the cloud a safe place to do business and a more enjoyable experience for enterprise users. Zscaler’s purpose-built security platform puts a company’s defenses and controls where the connections occur—the internet—so that every connection is fast and secure, no matter how or where users connect or where their applications and workloads reside.

Position - Senior Backend Engineer

Location - San Jose, CA

We are seeking a Backend Engineer with a strong foundation in AWS, cloud service deployment, and machine learning (ML) model deployment, including large language models (LLMs). This role requires a blend of expertise in cloud computing, backend development, and machine learning technologies to support Zscaler's cutting-edge cloud-native platform.

Responsibilities/What You’ll Do

1. Develop and deploy scalable, high-availability cloud services and applications, emphasizing AWS, GCP, Azure, Snowflake, etc.
2. Implement and manage the deployment of machine learning models, with a focus on efficiency and scalability.
3. Design and maintain ML service infrastructure, including data pipelines, model training orchestration, and monitoring systems.
4. Work closely with cross-functional teams to design, develop, and optimize backend solutions that meet business requirements.
5. Ensure system reliability, security, and performance through robust engineering practices.
6. Improve, and implement data engineering & analytics engineering best practices. Expert in CICD pipelines, able to mentor and guide others to adoption and use.
7. Collaborate with Data Engineering, Analytic engineering & BI teams and perform complex data analysis to design physical data models and mappings from business requirements.
8. Hands-on in designing & developing key initiative data pipelines to integrate various applications using supported APIs & model the data in cloud data warehouse to support the reporting requirements.
9. Perform code reviews, manage code performance improvements, and teach standards for code maintainability.
10. Propose ideas to improve the scale, performance, and capabilities of the Data Platform.

Qualifications/Your Background

1. Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
2. 5+ years of experience in backend development, with extensive knowledge in cloud services deployment.
3. Demonstrated experience with AWS, GCP, Azure, Snowflake or Databricks and familiarity with Docker and Kubernetes.
4. Strong hands-on experience in modern data stack tools like Matillion, DBT.
5. Completely proficient in advanced SQL, Python/Snowpark/PySpark/Scala (any Object Oriented language Concepts), ML libraries.
6. Must have hands-on experience in Python to extract data from APIs, build data pipelines.
7. Proficiency in programming languages such as Python, Java, or Node.js, and experience with machine learning frameworks like PyTorch and TensorFlow.
8. Experience in deploying and managing machine learning models in production environments.
9. Strong problem-solving skills, with the ability to work independently in a fast-paced Agile environment.

Desired Skills

1. Experience in algorithm model engineering, AI product implementation, LLM, image generation, etc., is preferred.
2. Extensive experience working with Python and Streamlit.
3. Proficiency in building data pipelines to integrate business applications (salesforce, Netsuite, Google Analytics etc) with Snowflake.

Zscaler’s salary ranges are benchmarked and are determined by role and level. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations and could be higher or lower based on a multitude of factors, including job-related skills, experience, and relevant education or training.

The base salary range listed for this full-time position excludes commission/ bonus/ equity (if applicable) + benefits.

Base Pay Range

$140,250 — $165,000 USD

By applying for this role, you adhere to applicable laws, regulations, and Zscaler policies, including those related to security and privacy standards and guidelines.

Zscaler is proud to be an equal opportunity and affirmative action employer. We celebrate diversity and are committed to creating an inclusive environment for all of our employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy or related medical conditions), age, national origin, sexual orientation, gender identity or expression, genetic information, disability status, protected veteran status or any other characteristics protected by federal, state, or local laws.

See more information by clicking on the Know Your Rights: Workplace Discrimination is Illegal link.

Pay Transparency

Zscaler complies with all applicable federal, state, and local pay transparency rules. For additional information about the federal requirements, click here.

Zscaler is committed to providing reasonable support (called accommodations or adjustments) in our recruiting processes for candidates who are differently abled, have long term conditions, mental health conditions or sincerely held religious beliefs, or who are neurodivergent or require pregnancy-related support.