Technical Lead - Message Security Detection

About the role

This role focuses on building high-throughput, low-latency infrastructure to support real-time threat detection. You will act as a technical anchor, architecting distributed data pipelines and cloud-native systems while driving AI-powered productivity initiatives across the engineering organization. The position requires deep ownership of backend services and detection systems to ensure reliability and performance at scale. You will guide the implementation of data pipelines that feed directly into machine learning model training workflows. Collaboration with cross-functional teams will translate business requirements into robust technical solutions. The role emphasizes mentorship and leadership in setting technical direction for engineering teams. You will champion the adoption of AI tools to accelerate development cycles and improve engineering efficiency.

Key facts

What you'll do

• Design and maintain backend services and detection systems that prioritize reliability and low latency.
• Build and optimize distributed data pipelines using Spark and Airflow to provide high-fidelity data for ML model training.
• Collaborate with Engineering Managers to set technical roadmaps, mentor engineers, and enforce high standards for system design and code quality.
• Integrate AI tools like GitHub Copilot, Claude, and OpenAI to improve internal development workflows and speed up the software lifecycle.
• Partner with Data Scientists, Security Researchers, Product Managers, and TPMs to turn business requirements into scalable technical solutions.
• Manage and optimize AWS and EKS infrastructure to ensure cost-efficiency and performance.
• Perform detailed system design work to address challenges around high throughput and latency constraints.
• Lead complex technical projects from conception to execution while providing architectural guidance to the team.
• Conduct in-depth performance debugging, benchmarking, and bottleneck resolution in large-scale production environments.
• Oversee the management and optimization of relational databases, particularly Postgres, at scale.
• Ensure that all implemented systems meet stringent security and operational reliability standards.
• Drive the adoption of best practices in engineering, focusing on code quality, maintainability, and scalability.

Requirements

• 8+ years of professional experience in backend development using Golang or Python.
• Expert proficiency in building distributed data pipelines with Airflow and Spark.
• Significant experience managing cloud-native applications on AWS, GCP, or Azure, including hands-on container orchestration with EKS.
• Proven ability to lead technical projects, mentor team members, and contribute to long-term architectural strategy.
• Strong system design skills with the ability to manage high throughput and latency challenges.
• Demonstrated ability to perform benchmarking, performance debugging, and bottleneck resolution in large-scale environments.
• Extensive experience working with Postgres or similar relational databases at scale.
• BS degree in Computer Science, Applied Sciences, or a related engineering field.
• Must be capable of designing infrastructure that supports real-time threat detection at scale.
• Should have a strong background in building and maintaining high-availability backend services.
• Must possess deep knowledge of cloud infrastructure and container orchestration platforms.
• Should demonstrate leadership qualities necessary for mentoring and guiding engineering teams.
• Must have a proven track record of delivering scalable and performant distributed systems.
• Should hold a strong understanding of security principles as they apply to data pipelines and backend services.

Nice to have

• Proficiency in TypeScript and React for internal tool development.
• Experience with data lakehouse architectures such as Snowflake or Databricks.
• Background in fraud prevention, network security, or threat detection.
• MS degree in Electrical Engineering or Computer Science.

Practical notes

• Compensation includes base salary, equity, and an annual bonus. The specific offer is determined by qualifications, experience, and location.
• This position involves access to technology subject to U.S. Export Administration Regulations (EAR). Candidates must be eligible to access controlled technology under U.S. law, and employment is contingent upon government authorization.
• The company uses AI-assisted tools to help recruiters prepare for interviews, though all hiring decisions are made by humans.
• Identity validation and video interviews are part of the standard recruitment process.
• Applicants must successfully complete pre-employment checks following a conditional offer.
• This is a full-time position based in Bangalore, India, with hybrid work arrangements.
• The role may require interaction with global teams across different time zones.
• Candidates should be prepared for a technically rigorous interview process focusing on system design and real-world problem-solving.
• Only candidates who meet the specified requirements will be considered for further stages.