Senior AI Infrastructure Engineer
Security and Networking
SeniorAIInfrastructureEngineer
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“Senior AI Infrastructure Engineer at Senior AI Infrastructure Engineer. Skills: AI Infrastructure Engineering, MLOps, Scalable Infrastructure Architecture, Production Deployment of AI Models and Agents, Python/C++ Proficiency, Cloud Platform Expertise, CI/CD Integration, Security in AI Systems. Architecting, developing and optimizing scalable infrastructure for deploying security and networking AI models and agents in production. Managing ML/agentic workflows to ensure performance, high availabi”
Industry & Context.
What They're Looking For.
Must Have
BSc/MSc in CS/CE or related field (or equivalent experience), At least 8 years of experience in ML engineering with a track record of deploying LLMs and agents to production at scale (including distributed environments), Proficiency in Python and/or C++, with a deep understanding of ML/AI frameworks, Hands-on experience with microservices, container orchestration, and cloud platforms for large-scale training and inference workloads, Knowledge of ML training and inference optimization techniques, Understanding of build infrastructure and CI/CD tools and practices (e. g. GitLab, GitHub Actions, Jenkins), Experience with teaching and mentoring, Proactive owner who takes pride in your work but remains humble and approachable, Excellent collaboration skills, with the ability to explain complex infra concepts to non-technical stakeholders clearly and kindly
Nice to Have
Experience deploying and optimizing generative models and multi-agent systems for performance, Deep systems knowledge (Linux internals, network protocols, or high-performance computing), A background in security research, including knowledge of firewalls, intrusion detection, or network architectures
What You'll Do.
developing and optimizing scalable infrastructure for deploying security and networking AI models and agents in production
Managing ML/agentic workflows to ensure performance
and cost-effectiveness
Designing and implementing pipelines and frameworks for AI training
Partnering with data scientists and security architects to operationalize AI agents
including packaging and integration with existing systems
Partnering with DevOps teams to integrate pipelines and workflows into CI/CD processes
ensuring reliable deployments and rollbacks
Building proactive monitoring systems to identify issues in quality and infrastructure before they impact production
Implementing access controls
authentication mechanisms
and encryption standards to keep our AI models and data secure
Documenting guidelines and leading knowledge-sharing sessions to elevate the team’s collective development expertise
How You'll Work.
Team & Collaboration
Collaborate closely with data scientists, software engineers, and security architects; Partnering with data scientists and security architects to operationalize AI agents; Partnering with DevOps teams to integrate pipelines and workflows into CI/CD processes; Excellent collaboration skills, with the ability to explain complex infra concepts to non-technical stakeholders clearly and kindly
Communication Scope
Ability to explain complex infra concepts to non-technical stakeholders clearly and kindly
Full Job Description
We're looking for a Senior AI Infrastructure Engineer to join a group that specializes in Security and Networking, and specifically ML/AI, MLOps, and agentic AI development. As a Senior AI Infrastructure Engineer, you’ll build and maintain the infrastructure, tools and processes necessary to support the AI lifecycle in a production environment. You will collaborate closely with data scientists, software engineers, and security architects to ensure smooth development, deployment, evaluation, and optimization of AI pipelines, models, and agents. This role requires a balance of high-level engineering rigor and a collaborative spirit; you’ll be a technical anchor and a supportive peer for teams across the organization. **What you’ll be doing:** * Architecting, developing and optimizing scalable infrastructure for deploying security and networking AI models and agents in production. * Managing ML/agentic workflows to ensure performance, high availability, resource efficiency, and cost-effectiveness. * Designing and implementing pipelines and frameworks for AI training, inference, and experimentation. * Partnering with data scientists and security architects to operationalize AI agents, including packaging and integration with existing systems. This includes contributing to and reviewing code, design documents, and test plans. * Partnering with DevOps teams to integrate pipelines and workflows into CI/CD processes, ensuring reliable deployments and rollbacks. * Building proactive monitoring systems to identify issues in quality and infrastructure before they impact production. * Implementing access controls, authentication mechanisms, and encryption standards to keep our AI models and data secure. * Documenting guidelines and leading knowledge-sharing sessions to elevate the team’s collective development expertise. **What we need to see:** * BSc/MSc in CS/CE or related field (or equivalent experience) * At least 8 years of experience in ML engineering with a track record
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