Senior AI Security Engineer

🕒 vor 11 Tagen

🇮🇳 Indien – Remote

⏰ Vollzeit

🟠 Senior

👮‍♂️ IT-Sicherheitsingenieur

👻 Geisterscore 10%

Was es bedeutet: die Wahrscheinlichkeit, dass für diese Stelle niemand wirklich einstellt.So liest du es: 60 % oder höher heißt, wir halten das für einen Geisterjob. Niedrigere Werte sind weniger bedenklich.Warum dieser Wert:

• Seit 11 Tagen offen.
• Stellen bei diesem Unternehmen werden meist in 21 Tagen besetzt.
• Kein Gehalt angegeben.

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Abacus Insights

WebsiteLinkedInAlle Stellen

51 - 200 Mitarbeiter

🏥 Gesundheitswesen

💼 Beratung

📦 Logistik

Healthcare • Consulting • Logistics

Abacus Insights ist ein führender Anbieter von Datenlösungen für Gesundheitspläne, der Gesundheitszahlern durch die Bereitstellung nutzbarer und interoperabler Daten neue Möglichkeiten eröffnet. Das Unternehmen bietet eine umfassende Suite von Datenlösungen, die darauf abzielen, komplexe staatliche Vorgaben zu adressieren und die Einsatzbereitschaft der Zahler zu verbessern. Die Plattform von Abacus Insights kann unterschiedliche Datenquellen konsolidieren und normalisieren, um umfassende Patientenakten zu erstellen, die Datenintegrität zu gewährleisten und zeitnahe Datenaktualisierungen zu ermöglichen. Ihre Lösungen unterstützen verschiedene Anwendungsfälle, darunter Risikoadjustierung, klinischen Datenaustausch, Kostenmanagement und Leistungsberichterstattung. Mit einem Fokus auf Technologie und Gesundheitswesen unterstützt Abacus Insights Zahler dabei, Kosten zu verwalten und die Mitgliedererfahrungen durch verbesserte Datenmanagement-Fähigkeiten zu optimieren.

Beschreibung

• Serve as the senior security engineering partner for AI product initiatives from concept and architecture through implementation, deployment, monitoring, and production support • Translate roadmap and customer priorities into secure technical solutions and practical AI security decisions • Design, build, and secure AI-enabled applications and reusable platform capabilities, including agents, agentic workflows, MCP servers and tools, SQL and RAG agents, model integrations, retrieval services, and customer-facing AI experiences • Contribute production-quality Python, security automation, reference implementations, tests, policy-as-code, and integration components • Define and implement security patterns for identity, authentication, authorization, least-privilege tool access, secrets management, tenant isolation, data classification, encryption, audit logging, telemetry, and human approval controls • Conduct architecture reviews and threat modeling for AI applications • Build security requirements and automated controls into GitLab CI/CD, code review, testing, deployment, and release processes • Partner with AI Engineering on model and application evaluation, logging, telemetry, and monitoring • Review and support secure implementation of MCP servers, APIs, AI tools, and data connections • Design and build private-by-default cloud foundations for AI knowledge services using multi-account environments, private connectivity, firewalled egress, encryption keys, and Terraform • Secure knowledge graph and retrieval platforms, including graph and vector stores, governed MCP tools, authorization, and backup and restore • Build and review MCP servers and gateway integrations with authentication, identity propagation, tool-level access policies, and audit logging • Secure ingestion and embedding pipelines integrating Confluence, Jira, GitLab, and SharePoint • Create secure paved-road templates for citizen-developed and AI-assisted applications and administer platform controls • Coach citizen developers through application registration, data classification, code scanning, secrets management, promotion, logging, and production readiness • Partner with Privacy, Compliance, and Legal on HIPAA, HITRUST, SOC 2, GovRAMP, ISO 27001, and GDPR requirements • Represent Abacus in customer-facing architecture and security conversations • Provide hands-on technical support for design changes, incidents, and client escalations

🎯 Anforderungen

• Minimum 5+ years of experience in software engineering, security engineering, platform engineering, DevSecOps, application security, or a related technical discipline, including hands-on responsibility for production systems supporting real customers • Demonstrated experience designing, building, deploying, or securing AI-enabled applications in production, with hands-on depth in at least one of agents or agentic workflows, MCP, RAG, or AI application security, and working exposure across the others • Strong software engineering fundamentals, including Python, API design and security, testing, code review, automation, deployment practices, incident response, and configuration management • Ability to contribute directly to application and platform implementation through code, reusable components, security tooling, CI/CD controls, technical documentation, and reference architectures • Experience securing cloud-native and distributed systems, including identity and access management, authorization design, secrets management, encryption, network and API controls, logging, monitoring, and secure data flows • Hands-on experience with AWS (or an equivalent cloud) security architecture, including multi-account organization design and service control policies, VPC and Transit Gateway networking, PrivateLink, network firewall policy, ECS Fargate and EC2, KMS, Secrets Manager, and centralized logging • Infrastructure as Code experience with Terraform, including policy scanning, OIDC-based CI/CD deploy roles, and repeatable account baselines • Experience with graph and vector data stores, with Neo4j and Cypher preferred and comparable graph or vector database experience considered • Practical knowledge of building and securing MCP servers and MCP gateways, including remote server authentication, OAuth/OIDC, enterprise SSO, and audit trails • Experience designing secure RAG ingestion pipelines, including content chunking and embedding, embedding model governance, index versioning, secrets and sensitive-data detection, and data classification tiers • Working knowledge of AI security risks and controls, including prompt injection, tool misuse, excessive permissions, sensitive-data exposure, insecure output handling, retrieval integrity, model and dependency risks, and auditability • Experience collaborating with senior engineers and technical leads during architecture and implementation • Experience reviewing third-party AI services, integrations, or connectors, including OAuth and API scope analysis, data-flow mapping, vendor security considerations, token lifecycle, data retention, and training-use terms • Working knowledge of secure SDLC and DevSecOps practices, including SAST, SCA, secrets scanning, threat modeling, risk acceptance, and automated deployment gates • Experience operating in regulated or high-trust environments such as healthcare, with working knowledge of HIPAA, HITRUST, SOC 2, ISO 27001, GDPR, GovRAMP, FedRAMP, or comparable frameworks • Ability to work US Eastern Time hours, with core hours of 9:00 AM to 5:00 PM ET, Monday through Friday • Bachelor's Degree in Computer Science, Computer Engineering, Cybersecurity, or a related field required

🏖️ Vorteile

• Competitive leave and benefits • Comprehensive health coverage • Equity for every employee – share in our success • Growth-focused environment – your development matters here

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