Generative AI Principal Python Engineer

March 12

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Trimble Inc.

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Dedicated to the world’s tomorrow, Trimble is a technology company delivering solutions that enable our customers to work in new ways to measure, build, grow and move goods for a better quality of life. Core technologies in positioning, modeling, connectivity and data analytics connect the digital and physical worlds to improve productivity, quality, safety, transparency and sustainability. From purpose-built products and enterprise lifecycle solutions to industry cloud services, Trimble is transforming critical industries such as construction, geospatial, agriculture and transportation to power an interconnected world of work.

Transportation & Logistics • Building Design, Construction and Operation • Natural Resources, Utilities and Government • Geospatial • Survey & Engineering

10,000+ employees

💰 Post-IPO Debt on 2022-12

📋 Description

• Design, develop, and maintain cutting-edge LLM-based agentic applications. • Collaborate across global teams and leverage agile methodologies. • Monitor performance using observability services like Datadog. • Keep track of the latest research in fine-tuning and prompt engineering. • Translate product requirements into scalable software designs. • Develop comprehensive test suites to ensure code quality. • Mentor junior engineers in LLM-based solution design and deployment. • Work in an agile environment, planning and executing sprints. • Employ CI/CD pipelines and maintain code versioning in GitHub.

🎯 Requirements

• Strong proficiency in Python programming language • Minimum 6 months experience working with GenAI applications • Strong communication skills since we work with a global team • Leadership and Mentoring: Guiding and mentoring other engineers • Providing technical expertise • Experience with cloud platforms (e.g Azure, AWS) • Knowledge of microservices architecture and containerization technologies (e.g., Docker, Kubernetes) • Experience with RESTful APIs and API design principles • Understanding of database management systems (e.g., NoSQL, PostgreSQL) • Proficiency with Git for version control • Managing code changes and collaborating with other team members • Maintaining a history of code revisions • Continuous Integration/Continuous Deployment (CI/CD): Tools like GitHub Actions • Integrating the automation into CI/CD pipelines • Problem-Solving and Analytical Thinking: Designing efficient automation solutions/frameworks • Ability to identify and troubleshoot complex software defects • Agile Methodologies: Agile methodologies such as Scrum or Kanban • Planning for Iterative development cycles • Manage frequent releases • Risk Assessment and Mitigation: Ability to identify and mitigate risks related to software quality • Measure how well risks are documented and managed throughout the project