What you will do
Architect & Scale:
Design and maintain high-throughput detection systems and backend services, ensuring low latency and high reliability.
Data Orchestration:
Lead the development of robust data pipelines using
Spark and Airflow
to supply detection teams with high-fidelity data for ML model training and evaluation.
Technical Leadership:
Partner with Engineering Managers to define technical roadmaps, mentor junior/mid-level engineers, and drive best practices in code quality and system design.
AI-Driven Innovation:
Lead the team in adopting
AI productivity initiatives
, leveraging tools like Claude, OpenAI, and GitHub Copilot to accelerate the development lifecycle and automate internal workflows.
Cross-functional Collaboration:
Work closely with TPMs, Product Managers, Data Scientists, and Security Researchers to translate complex business needs into scalable technical solutions.
Operational Excellence:
Manage and optimize cloud-native infrastructure on
AWS/EKS
, ensuring systems are cost-effective, secure, and performant.
Must Haves
8+ years of qualified experience:
Proven track record in production-level backend development with
Python or Golang
.
Data Engineering Expertise:
Expert-level proficiency in building and optimizing distributed data pipelines using
Spark and Airflow




(or equivalent orchestration tools).
Cloud & Infrastructure:
Extensive experience managing and scaling cloud-native applications on
AWS (highly preferred)
, GCP, or Azure, with a
proven track record of hands-on container orchestration using EKS
.
Leadership & Mentorship:
Experience leading technical projects, mentoring engineers, and contributing to the long-term technical strategy of a team.
System Design:
Strong ability to design complex integrations and handle significant throughput/latency challenges.
Problem Solving:
A methodical approach to performance debugging, benchmarking, and resolving bottlenecks in large-scale systems.
Database Proficiency:
Strong experience with
Postgres
or similar relational databases at scale.
Education:
BS in Computer Science, Applied Sciences, or a related engineering field.
Nice to Haves
Frontend Literacy:
Familiarity with
React and TypeScript
to assist with internal tool visualizations.
Data Ecosystems:
Experience with
Databricks
, Snowflake, or similar data lakehouse architectures.
Cybersecurity Domain:
Background in threat detection, network security, or fraud prevention.
Advanced Degrees:
MS in Computer Science or Electrical Engineering.
#LI-AB2

📌 Senior Software Engineer (Tech Lead) - Message Security Detection (Bengaluru)
🏢 Abnormal
📍 Bengaluru