About The Position

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. 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.

Requirements

  • Bachelor's degree in Computer Science, Software Engineering, Information Systems, or a related discipline, or equivalent experience
  • 7+ years of software engineering, DevOps, platform engineering, or site reliability engineering experience
  • Proven experience owning production deployments for business-critical applications
  • Deep experience with Kubernetes and containerized application deployment
  • Experience designing and maintaining enterprise CI/CD pipelines
  • Strong experience with Infrastructure-as-Code technologies such as Terraform, Ansible, or similar tools
  • Experience operating cloud-based applications in Azure, AWS, or similar platforms
  • Experience implementing monitoring, logging, alerting, and observability solutions
  • Experience with security, secrets management, identity integration, and RBAC
  • Experience deploying and operating AI-powered applications in production environments
  • Experience with LLM-based applications, AI agents, AI orchestration frameworks, vector databases, or similar technologies
  • Experience using AI-assisted development tools to improve infrastructure automation, deployment engineering, troubleshooting, and operational efficiency
  • Strong written and verbal communication skills

Nice To Haves

  • Experience deploying multi-agent systems in production
  • Experience with AI orchestration frameworks such as Semantic Kernel, LangGraph, CrewAI, AutoGen, OpenAI Agents SDK, or similar technologies
  • Experience deploying and operating MCP-based systems and tool ecosystems
  • Experience with AI observability platforms such as LangSmith, LangFuse, Arize, Phoenix, or similar tools
  • Experience operating hybrid cloud and on-premises environments
  • Experience mentoring less experienced engineers
  • Energy industry experience

Responsibilities

  • 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

Benefits

  • competitive compensation
  • strong career path
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