Software Engineer, AI & Developer Experience (Principal - Advisor - Sr Advisor)
- Compensation
- Not disclosed
- Location
- Not listed
- Work setup
- Not specified
- Seniority
- Principal
- Employment
- Part time
- Experience
- Not specified
- Category
- Software engineering
- Posted
Skills
Must have
- An undergraduate degree in Computer Science, Software Engineering, Computer Engineering, or a similar technical discipline.
- A minimum of seven years of related experience, including professional software-development experience.
- Demonstrated experience designing, developing, testing, troubleshooting, securing, documenting, and maintaining software solutions.
- Experience with software engineering workflows such as source control, build automation, automated testing, code review, continuous integration, continuous delivery, or release automation.
- Experience developing or improving software architecture, engineering tools, reusable technical solutions, or development practices in a complex software environment.
- Ability to operate under broad direction, lead technically complex initiatives, collaborate across engineering functions, and influence technical decisions without relying on direct organizational aut
Nice to have
- Experience in Developer Experience, developer productivity, engineering enablement, platform engineering, or internal developer platforms.
- Hands-on experience with AI-assisted software-development tools, coding assistants, AI development agents, agentic workflows, or integrations between AI systems and engineering platforms.
- Experience designing reproducible or deterministic development environments, build systems, repository standards, or repository-governance solutions.
- Experience integrating developer tools with source-control, CI/CD, issue-management, security, feature-management, collaboration, or observability platforms.
- Experience creating reference architectures, technical standards, engineering scorecards, automated repository assessments, or reusable implementation patterns across multiple software-development tea
Full description
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 Landmark
Landmark, a Halliburton business line, provides the industry’s most comprehensive suite of digital solutions for exploration, drilling, and production optimization. Its software and data platforms empower customers to model subsurface assets, manage drilling risk, and accelerate decision-making through cloud, AI, and advanced analytics.
About the Role
Landmark is seeking a Principal Software Engineer, AI & Developer Experience to define and build the tools, architectures, and engineering practices that enable software engineers and AI development agents to work together effectively. The role spans the complete software development experience, from local development environments and source repositories through build, test, code review, continuous integration and delivery, and the engineering platforms connecting these activities.
This is a hands-on technical leadership role at the intersection of software architecture, Developer Experience, and AI-enabled software development. The successful candidate will lead large-scale engineering initiatives, create reusable tools and reference implementations, improve complex repositories and development systems, and establish the technical foundations for AI-enabled software development across Landmark.
Key Responsibilities
- Define the architecture for AI-enabled software development across Landmark, including how software engineers, AI agents, developer tools, source control, CI/CD systems, and internal engineering platforms work together.
- Establish technical standards for a high-performing developer environment, including local development, build and test workflows, deterministic environments, repository conventions, documentation, and machine-readable interfaces for AI development agents.
- Design and build an AI tooling layer that connects engineers and AI agents with source control, collaboration tools, issue tracking, CI/CD, code review, feature management, security, observability, and internal developer platforms.
- Lead hands-on technical pilots and reference implementations in production software repositories to validate architectural approaches, address complex engineering challenges, and establish repeatable patterns that other development teams can adopt.
- Create automated repository assessments, engineering health indicators, productivity signals, and technical scorecards that identify risks, inconsistencies, and opportunities to improve the developer experience.