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Date: Jul 24, 2026

Location: Calgary, AB, CA, T2P 3V4

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 up-to-date 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 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 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

Candidates having qualifications that e

📌 Senior Platform Engineer (Calgary)
🏢 Halliburton
📍 Calgary