I
Inetum
MLOps
Site Reliability Engineer (AI & GenAI)
On-siteSeniorMLOpsJust posted
Role summaryAI-generated
This role focuses on ensuring the reliability and performance of AI and Generative AI applications across all environments, implementing monitoring and alerting solutions. The engineer will define SLOs, manage incidents, and drive automation to maintain high availability for critical business services.
Skills required
About this role
Do you want to play a key role in the evolution of AI and Generative AI platforms that support critical business services? We are looking for a Site Reliability Engineer (AI & GenAI) to ensure the reliability, availability, and performance of AI-powered solutions while contributing to the modernization and automation of production environments.
Key Responsibilities:
- Ensure the operation, stability, and availability of critical AI/GenAI applications across Development, UAT, Pre-Production, and Production environments.
- Implement and manage monitoring, alerting, and dashboard solutions to maintain high levels of performance and service reliability.
- Define and monitor reliability metrics, including SLIs, SLOs, and Error Budgets, fostering a strong Site Reliability Engineering culture.
- Participate in incident management, troubleshooting, problem resolution, and on-call activities, ensuring SLA compliance.
- Conduct post-incident reviews and implement corrective and preventive actions to improve platform resilience.
- Automate operational processes, deployments, and support activities through scripting, CI/CD pipelines, and Infrastructure as Code practices.
- Contribute to platform modernization initiatives, promoting containerization, automation, and DevOps best practices.
- Collaborate closely with Development, Cloud, Infrastructure, Security, Network, and Database teams.
- Drive continuous improvement initiatives focused on performance optimization, scalability, capacity management, and cost efficiency.
Qualifications
- Proven experience in Site Reliability Engineering, DevOps, Production Engineering, Application Operations, or Production Support roles within complex enterprise environments.
- Strong knowledge of Linux/Unix systems, application troubleshooting, and production operations.
- Experience supporting and operating applications built with Python/FastAPI, APIs, cloud-native services, or similar technologies.
- Hands-on experience with automation and scripting using Python, Bash, or similar languages, as well as CI/CD pipelines and release automation.
- Solid understanding of Docker, Kubernetes, and Infrastructure as Code tools such as Terraform.
- Experience working with cloud platforms, preferably Microsoft Azure.
- Knowledge of observability, monitoring, and log management tools such as Dynatrace, Splunk, or equivalent solutions.
- Familiarity with SRE principles and practices, including SLIs, SLOs, Error Budgets, Postmortems, and toil reduction.
- Experience contributing to cloud transformation, platform modernization, or operational excellence initiatives.
- Understanding of databases, storage solutions, and distributed systems, including technologies such as PostgreSQL, pgvector, Azure Blob Storage, or similar.
- Fluent English (minimum B2 level). French is considered a plus.
Nice to Have:
- Experience with AI/GenAI ecosystems, RAG pipelines, vector databases, LiteLLM, or AI platform operations.
- Knowledge of Azure AI Services, Azure AI Foundry, and Document Intelligence solutions.
- Experience with hybrid cloud environments, virtualization technologies, or on-premises Kubernetes platforms.
- Exposure to Agile methodologies and technical leadership activities.
Personal Skills:
- Strong sense of ownership, autonomy, and accountability.
- Service-oriented mindset with a focus on reliability and operational excellence.
- Excellent analytical and problem-solving skills.
- Ability to collaborate effectively within multidisciplinary and international teams.
- Strong communication skills, with the ability to explain technical concepts to a variety of stakeholders.
- Comfortable working in fast-paced, demanding, and continuously evolving environments.
Additional Information
- Workplace type: Hybrid (50% onsite, 50% remote).
- Location: Parque das Nações, Lisboa.
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