Senior Platform Engineer - AI Platforms & Deployment - Landmark

We are looking for the right people — people who want to innovate, achieve, grow and lead. We attract and retain the best talent by investing in our employees and empowering them to develop themselves and their careers. Experience the challenges, rewards and opportunity of working for one of the world’s largest providers of products and services to the global energy industry. About the Role You will be responsible for the deployment, operation, and reliability of next-generation AI-enabled software platforms. Our products combine modern web applications, cloud-native services, and agentic AI frameworks that coordinate multiple specialized agents and tools to automate complex geoscience workflows. This role sits at the intersection of software engineering, infrastructure engineering, AI platform operations, and DevOps. You will help define how applications move from development to production, working closely with software engineers, AI engineers, visualization engineers, and architects to build secure, scalable, and repeatable deployment workflows. You will design and maintain CI/CD pipelines, deployment automation, infrastructure-as-code, observability systems, and runtime environments that support both traditional enterprise applications and modern AI-driven systems. You will build software for the following domain: Geoscience - geology, geophysics, or petrophysics Technologies used may include: TypeScript, Python, Java, C#, and Go Angular, React, and Node.js Azure OpenAI and other AI platforms Agentic AI frameworks and orchestration platforms MCP-based architectures and tool ecosystems Azure and AWS cloud platforms Kubernetes, Docker, Helm Terraform, Ansible, Argo CD, Flux, GitHub Actions, Azure DevOps Pipelines PostgreSQL, SQL Server, MongoDB, Redis, Vector Databases Prometheus, Grafana, OpenTelemetry, ELK, Datadog, and other observability platform Job Duties Design and maintain CI/CD pipelines for web applications, services, and AI platforms Build and operate Kubernetes-based environments across development, testing, and production Develop Infrastructure-as-Code solutions that enable reliable and repeatable deployments Design deployment architectures for cloud, hybrid, and on-premises environments Deploy and operate AI-powered applications, agent runtimes, MCP servers, orchestration services, and supporting infrastructure Implement monitoring, logging, tracing, alerting, and operational dashboards Establish platform reliability, security, observability, and operational standards Automate build, deployment, validation, and release processes Troubleshoot and resolve production incidents across applications, infrastructure, and cloud environments Apply security best practices and participate in architecture and security reviews Qualifications Bachelor's degree in Computer Science, Software Engineering, Information Systems, or a related discipline, or…