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.
- 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.
- Workplace type: Hybrid (50% onsite, 50% remote).
- Location: Parque das Nações, Lisboa.