Senior Platform Engineer in Calgary

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
• Prometheus, Grafana, OpenTelemetry, ELK, Datadog, and other observability platforms

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 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

Preferred

• 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 is not required but is a strong plus

How You Work

The engineer who succeeds in this role brings independent judgment to their work and applies it consistently. You own your assignments end to end, communicate clearly when something is off track, and treat code reviews as a genuine quality tool rather than a formality. You are comfortable working across time zones, adaptable when requirements shift, and focused on delivery outcomes rather than task completion. You pick up new tools and techniques on your own, evaluate them critically, and bring the ones that work to your team. You help the engineers around you improve because you understand that team quality compounds over time.

Why Landmark

We build small, high-ownership teams and invest in the quality of every person on them. You will work in a business where software is the product, the work you do matters, and the standards are high. You will own real work that ships, learn from engineers who push you, and grow into the kind of engineer the team relies on. We offer competitive compensation, a strong career path, and a role where you own what you build, and your impact is visible.

Halliburton is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, disability, genetic information, pregnancy, citizenship, marital status, sex/gender, sexual preference/orientation, gender identity, age, veteran status, national origin, or any other status protected by law or regulation.