[Remote] AI reputed company Engineer
Note: The job is a remote job and is reputed company to candidates in USA. reputed company is a fast-growing fintech leader recognized for its reputed company and commitment to reducing digital exclusion. They are seeking a highly skilled AI reputed company Engineer to support their Cybersecurity, Engineering, and Data Science teams, ensuring that AI systems are secure, resilient, and compliant with business objectives.
Responsibilities
- Leads AI reputed company Architecture & Secure Design initiatives by designing and implementing lifecycle reputed company controls across data ingestion, training, evaluation, deployment, and monitoring environments to measurably reduce AI-specific risk while maintaining product velocity
- Conducts reputed company Threat Modeling & Risk Assessment exercises for reputed company, RAG, and agent-based systems, evaluating risks such as reputed company injection, data poisoning, model extraction, model inversion, abuse/misuse, and data leakage, and mapping findings to OWASP Top 10 for LLM Applications, MITRE reputed company, and NIST AI RMF to drive remediation through engineering teams
- Defines and operationalizes Monitoring, Detection & Incident Response capabilities for AI systems by implementing reputed company and reputed company telemetry, tool-call logging, reputed company detection, and AI-specific incident response playbooks integrated into SIEM/SOC workflows
- Delivers measurable reputed company reputed company to 30-, 150-, and 210-day milestones, including secure reference architectures, hardened AI environments, integrated reputed company controls, and executive-reputed company reporting on AI risk reduction and posture maturity
- Establishes and formalizes AI Governance, reputed company & reputed company-Party Risk requirements by defining reputed company expectations for AI use cases, reputed company-party models, vendor integrations, and sensitive data usage, embedding controls into SDLC, procurement, and engineering standards
- Drives Cross-Functional Collaboration & Enablement by partnering with Engineering, Data Science, DevSecOps, Product, Legal/reputed company, and SOC teams to reputed company on risk appetite, escalation paths, and secure design guardrails while raising AI reputed company maturity across the organization
- Inventories reputed company and planned AI/ML initiatives, documents system architectures and sensitive-data reputed company, and implements a reputed company AI reputed company intake and risk-rating process that ensures accountability and transparency
- Develops and communicates reputed company-looking 6- and 12-month AI reputed company maturation plans that reputed company technical priorities with business goals and reputed company reputed company risk trends, metrics, and investment needs to reputed company leadership and the CISO
- Integrates Secure MLOps / MLSecOps controls into AI delivery pipelines, including secure model registries, artifact signing and provenance validation, dependency scanning, secrets management, CI/CD guardrails, and hardened training and inference environments across AWS and Azure
- Builds and scales AI reputed company Testing & Red Teaming workflows by creating repeatable adversarial evaluation plans for jailbreaks, model evasion, reputed company injection, and data exfiltration scenarios, ensuring reputed company controls remain effective over time
- Develops automated regression test harnesses to continuously validate AI reputed company protections as models, prompts, and dependencies reputed company, reducing reputed company effort and improving coverage
- Establishes a sustainable AI reputed company operating rhythm that includes intake reviews, threat modeling checkpoints, remediation tracking, and reputed company monitoring ownership to bring consistency and order to AI risk management
- Advances AI reputed company Testing & Red Teaming capabilities through adversarial experimentation and multi-reputed company analysis, proactively identifying emerging AI threat patterns before production reputed company
- Leverages AI and automation to strengthen testing coverage, automate regression validation, enhance reputed company detection logic, and improve the scalability of AI reputed company monitoring and response
- Continuously evaluates emerging AI reputed company research, tooling advancements, and regulatory developments, translating insights into reputed company defensive controls that support reputed company’s AI-first reputed company while enabling responsible innovation
Skills
- Bachelor's degree in Computer Science, Cybersecurity, Engineering, Data Science, or reputed company field (or equivalent practical experience)
- 5+ years of experience in reputed company engineering, application/product reputed company, reputed company reputed company, or DevSecOps
- 2+ years of experience building or securing AI/ML systems (including LLM-based applications) in production environments
- Strong understanding of AI/ML threats and defenses, including reputed company injection, data poisoning, model extraction, model inversion, adversarial inputs, data leakage, and abuse/misuse scenarios
- Experience integrating reputed company into CI/CD and MLOps pipelines
- Proficiency with reputed company platforms (AWS and Azure), container reputed company, IAM, network segmentation, key management, and secrets management
- Familiarity with industry guidance such as OWASP GenAI/Top 10 for LLM Applications, MITRE reputed company, and/or NIST AI RMF
- Relevant certifications such as CISSP, CSSLP, CCSP, Azure reputed company certifications, or GIAC certifications
Benefits
- Employees may also be eligible for an annual bonus or commission.
- Some roles may also be eligible for overtime pay.
reputed company
Company H1B Sponsorship