Posted 08 July, 2026

Backend Eng-AI Security

Diverse Lynx India

Bangalore, Rajasthan, IN Full Time

Reference: 26-01149-575-2

Job Description

Backend Engineer – AI Security

Location: Bengaluru, India
Function: AI Security – Technology & Innovation Centre (TIC)
Employment Type: Full-time

Role Purpose

The Backend Engineer – AI Security is responsible for designing and building scalable backend systems that support AI security research and solutions, including model lineage, provenance, policy enforcement, and security analytics services. The role focuses on APIs, data models, and backend services that enable research outputs to be operationalised as reliable platform components.

Key Responsibilities

Design and develop backend services and APIs to support AI security scanners, analytics, and platforms.
Implement data models and storage layers for model lineage, provenance graphs, and experiment metadata.
Build backend components to integrate research outputs such as fingerprinting, unlearning, and forensics.
Ensure scalability, reliability, and performance of AI security backend systems.
Collaborate with research engineers, applied researchers, and MLOps teams to enable end-to-end solutions.
Support integration with LG Security Platforms and enterprise deployment environments.
Contribute to backend documentation, service definitions, and technical design artefacts.

Required Qualifications & Experience

Education:

Bachelor's or Master's degree in Computer Science, Software Engineering, or a related engineering discipline.

Experience:

4–7+ years of experience in backend or platform engineering roles.
Experience building APIs and data-driven backend systems for large-scale applications.

Required Technical Skills

Strong proficiency in backend programming languages such as Python, Java, or Go.
Experience building RESTful or gRPC APIs and microservices.
Strong understanding of data modelling, databases (SQL/NoSQL), and graph-based systems.
Experience integrating ML/AI systems with production backend services.
Familiarity with cloud-native architectures, containerisation, and CI/CD practices.
Exposure to AI security, data lineage, compliance, or governance systems is desirable.

Success Indicators

Reliable and scalable backend services supporting AI security research and platforms.
Successful integration of research capabilities into backend APIs and enterprise systems.

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