Senior - AI Deployment Engineer

Accountabilities: • Design and manage CI/CD pipelines for agentic environments, reducing the time between solution development and production delivery.

• Deploy conventional applications across platforms and distribution channels, including app stores, content delivery networks (CDNs), mobile release trains, feature flags, and blue/green service rollouts.

• Provision, automate, and maintain standardized development, staging, and production environments.

• Operate and manage model and AI agent serving infrastructure, ensuring production availability, performance, low latency, and scalability.

• Establish quality, security, and compliance gates throughout the delivery pipeline to validate solutions before release.

• Define and manage versioning strategies, release schedules, rollback procedures, and rapid recovery processes in case of production failures.

• Implement observability and monitoring for AI solutions, tracking system behavior, operational health, solution quality, performance, and token consumption.

• Manage AI FinOps activities by monitoring and optimizing inference costs, managing budgets, and implementing intelligent model routing to balance cost and performance.

• Secure production environments through access controls, data protection measures, and mitigation of AI-related risks, ensuring compliance with client requirements.

• Implement infrastructure guardrails to manage model risk and prevent inappropriate or unsafe agent behavior in production.

• Manage versioning and traceability for application packages, environment configurations, and model endpoints to support controlled releases and safe rollbacks.

• Share production insights with upstream engineering teams, particularly regarding costs, failures, and real-world performance, to support continuous solution optimization.

• Apply responsible AI, ethics, privacy, data security, and compliance practices throughout deployment and production operations.

Requirements:

• Strong experience or technical expertise in LLMOps , including the deployment and operation of large language models and AI-powered systems.

• Knowledge of DevOps engineering practices, including infrastructure automation, deployment management, and CI/CD.

• Understanding of Site Reliability Engineering (SRE), production reliability, availability, performance, and scalability.

• Experience or knowledge of AI security, access control, and production data protection.

• Familiarity with observability and monitoring practices for application and AI systems.

• Understanding of AI FinOps, inference cost management, and cost optimization techniques.

• Knowledge of infrastructure guardrails, AI safety, and approaches to mitigating risks associated with AI models and agents.

• Experience with continuous integration and continuous delivery (CI/CD) processes.

• Understanding of model routing and selection strategies to optimize performance and operational costs.

• Ability to manage production environments, release processes, versioning, and incident recovery.

• Strong problem-solving and collaboration skills, with the ability to communicate operational findings and work closely with AI engineering and delivery teams.

Nice to have:

• Knowledge of cloud computing concepts and architectures.

• Practical experience with Infrastructure as Code (IaC), particularly Terraform.

• Familiarity with Azure Container Apps.

• Understanding of scalability and connectivity considerations in distributed environments.

• Experience with code reviews and software quality practices.

• Knowledge of Kubernetes (K8s) and container-based infrastructure.

Benefits:

• Health and dental insurance.

• Meal and food allowances.

• Childcare assistance.

• Extended paternity leave.

• Access to gym, fitness, and wellness partnerships through Wellhub (Gympass) and TotalPass.

• Profit Sharing and Results Participation (PLR).

• Life insurance.

• Continuous learning opportunities through an internal learning platform.

• Discounts through a partner discount club.

• Free online resources dedicated to physical, mental, and overall well-being.

• Pregnancy and responsible parenting courses.

• Partnerships with online learning platforms.

• Access to a language-learning platform.

• Additional employee benefits and well-being initiatives.

How Jobgether works: We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team. We appreciate your interest and wish you the best! Why Apply Through Jobgether?

Data Privacy Notice: By submitting your application, you acknowledge that Jobgether will process your personal data to evaluate your candidacy and share relevant information with the hiring employer. This processing is based on legitimate interest and pre-contractual measures under applicable data protection laws (including GDPR). You may exercise your rights (access, rectification, erasure, objection) at any time.

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