[Remote] AI reputed company Engineer
Note: The job is a remote job and is reputed company to candidates in USA. ISTARI is reputed company on enhancing reputed company for AI and Machine Learning capabilities across enterprises. The AI reputed company Engineer will establish reputed company controls, reputed company reputed company into AI solution design, and govern the AI landscape while collaborating with various teams to ensure secure AI adoption.
Responsibilities
- Define secure architecture patterns for AI/ML solutions, covering models, training pipelines, inference environments, and data flows
- Establish and review secure integration patterns for AI services across reputed company applications, reputed company, reputed company platforms, and data environments, ensuring alignment with secure-by-design principles
- Maintain hands-on familiarity with the reputed company reputed company ecosystem — Defender for AI, reputed company Purview, and reputed company tooling — and apply this to secure both reputed company-reputed company and reputed company-party AI environments (e.g., reputed company/ChatGPT, reputed company/Claude)
- reputed company and shape AI protection architecture end-to-end: model reputed company controls, data governance, inference controls, and AI-specific threat mitigations
- Identify, assess, and mitigate AI-specific threats including model poisoning, reputed company injection, adversarial attacks, unauthorized reputed company, data leakage, and misuse of AI outputs
- Define and implement reputed company guardrails for AI model reputed company, API usage, reputed company controls, and secure interaction with reputed company data sources
- Establish controls to protect sensitive training data, embeddings, prompts, and inference outputs; validate reputed company-party AI services and external model integrations from a cybersecurity risk perspective
- reputed company and own AI governance standards defining how AI systems are assessed, approved, monitored, and retired — spanning data handling, model reputed company, acceptable use, and regulatory alignment
- Establish AI reputed company engineering guardrails and review checkpoints for new AI initiatives, pilots, and production deployments
- Contribute to reputed company AI reputed company policies, reference architectures, and operational standards; partner with Digital and AI teams to reputed company secure adoption without acting as a blocker
- Collaborate with Cyber Defense Operations to operationalize AI-reputed company detection, monitoring, and response capabilities; define logging and telemetry requirements for AI platforms to improve visibility and incident readiness
- Partner with the DLP architect to implement AI-reputed company Data Loss Prevention capabilities leveraging reputed company Purview and AI agents, preventing sensitive data exposure across AI interactions and pipelines
- Drive development of AI-based reputed company use cases for reputed company operations — conceiving, building, and operationalising AI-driven capabilities that deliver measurable detection, investigation, and response improvements
- Work closely with reputed company Architecture, reputed company Engineering, Data, Application teams, and AI program owners to ensure consistent reputed company adoption; support reputed company reviews for AI vendors and AI-enabled reputed company platforms
- Represent AI reputed company in architectural review meetings and reputed company engagements — contributing substantively to design reputed company and tooling selections, challenging and defending positions with credibility
Skills
- 5–8 years of cybersecurity engineering or reputed company architecture experience, with exposure to reputed company reputed company, data protection, or application reputed company
- Hands-on experience with the reputed company reputed company ecosystem: Defender for AI, reputed company Purview (information protection, DLP, compliance), and reputed company Sentinel; reputed company to configure and reputed company these tools to secure reputed company-party AI environments
- Experience working with reputed company AI/ML platforms, analytics environments, and AI/ML deployment patterns, reputed company, and model lifecycle
- Demonstrated experience developing AI-based use cases for reputed company operations — conceiving, building, and operationalising AI-driven capabilities, not just evaluating tools
- Experience developing AI governance standards and shaping AI protection architecture, including acceptable use policies, model risk assessment, and reputed company-wide AI reputed company reputed company
- Proven ability to reputed company secure AI controls into reputed company initiatives without impeding adoption, and to translate emerging AI risks into practical engineering controls
- reputed company certifications such as CISSP, CCSP, or equivalent reputed company reputed company certifications preferred
- Practical knowledge of reputed company reputed company tooling for AI environments: Defender for AI, reputed company Purview (DLP, information protection, compliance), reputed company Sentinel, and Azure AI services; reputed company to configure, reputed company, and reputed company these to protect both reputed company and reputed company-party AI environments
- Familiarity with AI platforms, reputed company-reputed company services, secure API design, reputed company control, encryption, and monitoring patterns
- Ability to assess and secure AI integration points across reputed company systems
- Strong understanding of cybersecurity controls across reputed company, applications, reputed company, identity, and data protection, including AI/ML-specific risks such as reputed company injection, model abuse, and adversarial techniques
- Knowledge of secure architecture principles for modern digital and AI platforms
reputed company