Drive cross-PR&D security alignment, lead complex security design reviews, and shape the security architecture of our strategic cross-technology initiatives.
Responsibilities
Drive cross-PR&D alignment of the Secure Software Development Lifecycle (SSDLC), establishing consistent standards, controls, and practices across all engineering groups.
Lead complex security design reviews for new technologies, systems, services, and strategic cross-tech initiatives.
Define and own the security architecture for high-impact cross-team initiatives, ensuring security is embedded from the earliest design stages.
Serve as the security counterpart to PR&D architects- representing security in architecture forums, design discussions, and strategic technology decisions.
Partner with DevOps, Infrastructure, Platform, and R&D teams to integrate security into CI/CD pipelines, infrastructure-as-code, and shared platform services.
Requirements
Nice to have: high-scale distributed SaaS environments
Lead enterprise data engineering for a cloud-based Data Lake/Lakehouse environment, designing and implementing Medallion architectures, data pipelines, and governance standards.
Responsibilities
Design, implement, and evolve the organization’s enterprise Data Lake/Lakehouse architecture
Build scalable ELT/ETL pipelines using cloud-native technologies
Design dimensional models and semantic layers for BI and analytics
Implement data quality, lineage, cataloging, and metadata management best practices
Optimize data storage, query performance, and workload management
Requirements
Bachelor’s degree in computer science, MIS, engineering, or related field
The Sr AI Platform Infrastructure Engineer is a pivotal position for driving the strategic vision and technical execution for the Cancer Diagnostics AI/ML platform. The role is accountable for the architecture, reliability, scalability, security and cost of every layer beneath the platform's applications, from the cloud, network and compute foundation to the serving, orchestration and streaming systems that workloads run on.
Compensation
The base pay for this position is $99,300.00 – $198,700.00
Responsibilities
Design and own the platform's cloud and Kubernetes foundation, including account and network topology, VPC and subnet design, private connectivity, ingress and egress control, DNS and certificates, and the provisioning, upgrade, migration, multi-tenant isolation and security of production clusters.
Lead the platform's expansion across clusters and regions, covering topology, identity federation, state and data placement, traffic management and failure domains, and evaluate multi-cloud where business need warrants it.
Own infrastructure-as-code and GitOps for the platform, including module design, state management, environment promotion, drift control, and the testing and rollback of infrastructure changes; build and operate the CI/CD and deployment tooling that platform software releases run on in partnership with the AI Platform Software lead.
Architect, build and operate production model serving and GPU infrastructure for large language and predictive models, including scheduling, multi-tenancy, autoscaling, low-latency serving, inference optimization (quantization, batching, graph compilation), and capacity planning and cost attribution for shared compute.
Design, build and run AWS platforms behind mission systems for Australian Government and National Security customers, delivering infrastructure as code and ensuring security by design.
Responsibilities
Write, review and maintain best-practice CloudFormation templates from scratch, including nested stacks, StackSets and custom resources
Build, configure and operate AWS CodePipeline delivery for infrastructure and applications
Administer Git and CodeCommit: repository structure, branching strategy, access control and code review
Commission and deploy AWS services as code, including EC2, ECS, EKS, Secrets Manager, Private CA, ElastiCache (Redis), Amazon MQ (RabbitMQ), RDS and OpenSearch
Build security into every deployment: least-privilege IAM, encryption, network segmentation, logging and policy-as-code checks
Requirements
Nice to have: SIEM administration (Splunk, Elastic, Microsoft Sentinel)
Nice to have: ITSM platform administration (ServiceNow, Jira Service Management)
Nice to have: Threat intelligence platform administration (MISP, OpenCTI)
Nice to have: Linux and Windows system administration
Nice to have: ISM, Essential Eight, IRAP assessments
Lead technical engagement with Nebius' most strategic customers across the Gulf region, focusing on complex presales, large-scale ML workloads, and end-to-end customer solution ownership.
Responsibilities
Own end-to-end technical presales and solution delivery for strategic and enterprise customers across the Middle East, from initial discovery through PoC, architecture design, and production readiness.
Serve as a trusted technical advisor to senior customer stakeholders (CTO, Head of ML, Platform Engineering, AI Infrastructure teams).
Lead complex ML/AI infrastructure and MLOps architectures, including large-scale training and inference workloads on GPU-accelerated cloud platforms.
Design, validate, and document reference architectures, Infrastructure-as-Code solutions, and best-practice deployment patterns using Nebius AI.
Drive and execute advanced PoCs, workshops, architecture reviews, and executive-level presentations to demonstrate value and accelerate customer adoption.
Requirements
Nice to have: Hyperscale cloud providers experience
The Security Analytics Engineer designs, operates, and continuously improves the organization's security telemetry, analytics, detection engineering, and observability capabilities.
Locations (3)
Colombia
Costa Rica
Mexico
Responsibilities
Design and operate scalable security analytics platforms and telemetry pipelines.
Integrate, normalize, enrich, and correlate telemetry from endpoint, identity, cloud, application, infrastructure, network, and AI-enabled systems.
Develop and tune behavioral detections, correlation logic, dashboards, and alerting strategies.
Translate threat intelligence, incidents, vulnerability findings, and offensive-security results into improved detection content.
Build observability for AI agents and autonomous workflows, including identity, tool usage, execution activity, and security-relevant behavior.
Lead the Platform Security function and a globally distributed team of 30+ security engineers and specialists, setting priorities, accountabilities and quality standards while coaching and developing talent.
Responsibilities
Lead the Platform Security function and a globally distributed team of 30+ security engineers and specialists, setting priorities, accountabilities and quality standards while coaching and developing talent.
Drive the security engineering roadmap and service portfolio across data, infrastructure, endpoint, cloud, network, OT, AI, vulnerability management, security operations and SSDLC.
Partner with Security Architecture to translate security strategy and requirements into technical designs and controls.
Own the lifecycle and performance of security platforms and services, including service objectives, support models, monitoring, maintenance and recovery practices.
Develop security telemetry, detection engineering and response automation capabilities with Cyber Defense; improve vulnerability visibility and remediation workflows.
Requirements
Relevant university degree or equivalent experience
Lead the end-to-end engineering, build, configuration, integration, certification, deployment, and operationalization of a third-party AI-powered penetration testing platform within the enterprise environment.
Compensation
NTT DATA provides a reasonable range of compensation for U.S.-based positions. The starting pay range for this role is $102,675.00 - $171,125.00. Actual compensation will depend on a number of factors, including the candidate’s relevant experience, technical skills, and other qualifications.
Responsibilities
Lead end-to-end engineering of the platform
Provision and configure required infrastructure and platform components
Own technical certification process
Develop and maintain platform architecture diagrams and documentation
Serve as primary technical interface with third-party vendors
Requirements
Bachelor's degree in Computer Science, Information Security, Cloud Engineering, or a related technical field
Partner with the AI Platform Software and Safety leads on the model lifecycle by providing the infrastructure it runs on, including reproducible data, feature and training pipelines with dataset-to-model lineage, promotion environments, the traffic-shifting and rollback mechanisms behind canary, shadow and A/B rollout, and pipeline enforcement of the evaluation and promotion gates.
Requirements
Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field
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