Senior Software Engineer

About the role

You will architect and own the high-throughput, low-latency data infrastructure that powers real-time threat detection at massive scale. This role is focused on designing the architectural blueprint for distributed data pipelines and cloud-native infrastructure that convert raw data into high-fidelity, actionable intelligence. You will serve as the technical anchor, bridging complex system design with strategic execution across data and application teams. A core part of this mission involves leading our AI productivity initiatives to supercharge how the entire engineering team builds, tests, and ships software. You will mentor the next generation of engineers while defining the future of our data ecosystem through deep technical ownership. If you are passionate about driving technical strategy and building the foundation for ML models and security researchers, this is your mission.

Key facts

What you'll do

Architect and scale detection systems and backend services to ensure low latency, high reliability, and massive throughput across critical data paths.

Lead the development and optimization of data pipelines using Spark and Airflow to deliver high-fidelity data for ML model training and evaluation.

Partner with Engineering Managers to define technical roadmaps, mentor junior and mid-level engineers, and drive best practices in code quality and system design.

Lead the adoption of AI productivity initiatives, leveraging tools such as Claude, OpenAI, and GitHub Copilot to accelerate development lifecycle and automate internal workflows.

Collaborate closely with TPMs, Product Managers, Data Scientists, and Security Researchers to translate complex business requirements into scalable technical solutions.

Manage and optimize cloud-native infrastructure on AWS and EKS to ensure systems remain cost-effective, secure, and performant under load.

Design and maintain backend services that integrate complex systems while balancing scalability, maintainability, and operational constraints.

Drive performance debugging, benchmarking, and bottleneck resolution across large-scale distributed pipelines and data platforms.

Own end-to-end delivery of data platform features, coordinating with cross-functional partners to align on priorities and timelines.

Champion operational excellence by implementing monitoring, observability, and reliability improvements across data and infrastructure layers.

Evaluate and prototype new tools and frameworks to modernize the data stack and improve developer productivity over time.

Ensure data pipeline robustness, fault tolerance, and data quality through rigorous testing and validation practices.

Contribute to long-term technical strategy by identifying risks, trade-offs, and opportunities in the evolving threat detection landscape.

Requirements

You bring 8+ years of professional experience with a proven track record in production-level backend development using Python or Golang.

You possess expert-level data engineering expertise, specifically in building and optimizing distributed data pipelines using Spark and Airflow or equivalent orchestration tools.

You have extensive experience managing and scaling cloud-native applications on AWS, with strong preference for hands-on work in container orchestration using EKS.

You have a history of leading technical projects, mentoring engineers, and contributing to long-term technical strategy within a growing team.

You demonstrate strong ability to design complex integrations and navigate significant throughput and latency challenges in production environments.

You apply a methodical approach to performance debugging, benchmarking, and resolving bottlenecks in large-scale, distributed systems.

You have strong experience with relational databases such as Postgres, particularly at scale with demanding query and write patterns.

You hold a BS degree in Computer Science, Applied Sciences, or a related engineering field that provides a foundational understanding of systems and software engineering.

Nice to have

Familiarity with frontend technologies like React and TypeScript to assist with internal tool visualizations and debugging interfaces.

Experience with data ecosystem platforms such as Databricks, Snowflake, or similar data lakehouse architectures.

Background in cybersecurity domains including threat detection, network security, or fraud prevention.

Pursuit of or completion of advanced degrees such as an MS in Computer Science or Electrical Engineering.

Practical notes

This role is based in Bangalore, India, within a hybrid work arrangement.

Travel requirements and visa sponsorship details are to be confirmed directly with the hiring team.