suzega8mo ago
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AI Trust & Security Engineer
EngineeringSecurity Engineer
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Quick Summary
Overview
What You’ll Do Develop, implement, and maintain secure AI systems, with a focus on integrating security from the ground up. Develop algorithms and build predictive models that incorporate robust security measures.
Technical Tools
awsazuregcpapi-designetlmachine-learningpublic-speaking
What You’ll Do Develop, implement, and maintain secure AI systems, with a focus on integrating security from the ground up. Develop algorithms and build predictive models that incorporate robust security measures. Preprocess data, ensuring the quality, accuracy, and security of data fed into models, including protection against data poisoning. Deploy and maintain AI models in production with secure configurations and continuous monitoring. Transform machine learning models into APIs that can be integrated with other applications, ensuring secure API design and implementation. Collaborate with Data Engineers to build and manage secure data pipelines for AI/ML workflows, adhering to "Zero Trust Security" principles. Work with AI Architects to ensure AI solutions meet business requirements, quality attributes, and stringent security standards. Implement and maintain the Trust Engine ("Trust by Design") framework within our AI stack, specifically focusing on: Deception Detection: Develop and integrate built-in detection mechanisms for hallucinations, adversarial prompts, and policy violations within AI models. Zero Trust Security: Ensure every agent, connector, and workflow operates under least-privilege principles, with full audit trails for all operations. Human-in-the-Loop: Design and implement mechanisms for escalation, approval, and override at every step of AI workflows, by default. Auditability & Forensics: Guarantee that every action, decision, and data flow is logged, explainable, and traceable for forensic analysis. Compliance Packs: Develop and integrate industry-specific modules for regulatory compliance (e.g., HIPAA, PCI, etc.) into the AI systems. Responsible AI: Establish and enforce Responsible AI (RAI) guardrails, ensure explainability of AI decisions, and implement continuous monitoring for ethical and fair AI operation. Requirements What you’ll Bring 10+ years of applicable experience with building secure AI/ML solutions for large Enterprises. Hands-on experience in lead roles architecting secure solutions at scale for cloud data platforms. Hands-on experience architecting and building secure, scalable, and flexible enterprise data projects in Azure, AWS or GCP. Strong governance and security management experience is required, especially in the context of AI/ML systems. Effective communication skills (verbal, written, presentation/public speaking). Strong analytical and problem-solving skills, with a focus on security challenges in AI. Ability to work effectively with international and multicultural teams and with all levels of management. What Happens Next: We will review applications. If shortlisted, you'll participate in two virtual interviews with our Trusted Interviewers. You will have to go through a coding interview. We will aim to complete our selection process within two weeks and notify you of our decision. Why This Matters At Suzega, we're not just building better AI—we're thinking about how AI can work better with people and society. Are you ready to help shape what AI can and should do? Do you want to use your technical skills to make a real difference? If so, we'd love to hear from you. This is more than a job. It's a chance to shape the future. Location: Work from anywhere in India Benefits Please review the Benefits & Perks section in our Team Member Handbook for comprehensive information.
Location & Eligibility
Where is the job
India
On-site within the country
Who can apply
Open to applicants worldwide
Listing Details
- Posted
- September 9, 2025
- First seen
- May 6, 2026
- Last seen
- May 9, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 14%
- Scored at
- May 6, 2026
Signal breakdown
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