Senior Backend Engineer – AI Security Platform | Ahmedabad

About the Company: An early-stage, high-growth AI security startup.

Position Overview:

We are looking for a Senior Backend Engineer to join our client’s core platform team and help architect, build, and scale the backend systems that power AI security products. You will work closely with AI/ ML researchers, security engineers, and product leads to translate cutting-edge AI security requirements into robust, production-grade services. This role offers the opportunity to contribute to systems that protect AI models deployed by some of the most critical organisations in the world.

Reporting To: Head of Engineering

Key Responsibilities:

• Design, develop, and maintain highly scalable, reliable, and secure backend services and microservices that form the core of the company’s AI security platform.
• Build and expose RESTful and gRPC APIs consumed by internal services, ML inference pipelines, and external enterprise customers.
• Architect event-driven data pipelines to ingest, process, and serve real-time telemetry from AI model monitoring agents deployed at client sites.
• Implement authentication, authorisation (OAuth 2.0, RBAC), and end-to-end encryption mechanisms across all platform services.
• Collaborate with AI/ML engineers to integrate model-scanning, adversarial detection, and threat-intelligence modules into production backend workflows.
• Lead technical design reviews, define system architecture decisions, and document engineering standards for the team.
• Conduct code reviews, enforce code quality, and mentor junior engineers on best practices in backend development and security engineering.
• Own the reliability and performance of production services: establish SLIs/SLOs, write runbooks, and lead incident response.
• Engage with DevOps/Platform Engineering to ensure CI/CD pipelines, containerisation (Docker/Kubernetes), and cloud deployments follow security-by-design principles.
• Stay current on emerging AI security threats (OWASP LLM Top 10, MITRE ATLAS) and incorporate defence patterns into platform design.

Education:

• B.E./ B.Tech in Computer Science, Information Technology, or a related engineering discipline.
• M.Tech or equivalent postgraduate degree is an advantage, but not mandatory.

Experience:

• 4–5 years of hands-on backend software development in production environments.
• Proven track record of owning services end-to-end: design, build, deploy, monitor, and iterate.
• Experience working in a security-focused, platform, or AI/ ML-adjacent product company is highly preferred.

Technical Skills – Core:

• Strong proficiency in Java (Spring Boot/ Quarkus) and Python (FastAPI/ Django/ Flask) — both languages in active use.
• Deep understanding of RESTful API design, gRPC, and asynchronous messaging patterns (Kafka, RabbitMQ).
• Solid experience with relational databases (PostgreSQL, MySQL) and NoSQL stores (MongoDB, Redis, Elasticsearch).
• Proficiency with containerisation (Docker) and orchestration (Kubernetes/ EKS/ GKE).
• Hands-on experience with cloud platforms: AWS, GCP, or Azure — including IAM, VPC, KMS, and secure storage.
• CI/ CD tooling: GitHub Actions, Jenkins, GitLab CI, or equivalent.

Security & AI Domain Knowledge:

• Working knowledge of application security fundamentals: OWASP Top 10, threat modelling, secure coding standards.
• Basic familiarity with AI/ML security concepts — adversarial attacks, model inference risks, prompt injection, and data poisoning — sufficient to make informed design decisions.
• Understanding of compliance and governance frameworks relevant to AI systems (ISO 27001, SOC 2, DPDP Act 2023) is a plus.

Soft Skills:

• Strong written and verbal communication skills in English; ability to articulate technical trade-offs to nontechnical stakeholders.
• High ownership mindset; comfortable leading initiatives and driving outcomes independently.
• Effective collaborator across distributed, cross-functional teams.

Nice-to-Have/ Preferred:

• Exposure to adversarial ML tools: ART (Adversarial Robustness Toolbox), Foolbox, CleverHans, or equivalent.
• Experience building or integrating LLM security guardrails (prompt injection filters, output scanners).
• Familiarity with SIEM/SOAR integrations and security telemetry pipelines.
• Open-source contributions or publications in AI security, backend systems, or applied ML.
• Certifications: AWS Certified Solutions Architect, CKAD, CEH, or equivalent.

What’s on Offer:

• Competitive compensation with performance-based bonuses.
• Equity/ ESOP participation in a high-potential AI security startup.
• Direct exposure to cutting-edge AI security research and enterprise-scale deployments.
• Collaborative, flat culture with strong engineering values.
• Hybrid work flexibility; modern office in Ahmedabad, Gujarat.
• Comprehensive health insurance (employee + family) and professional development budget.