Principal Software Engineer-AI

Role Overview

As a Principal Software Engineer, you will be a key contributor to the design, development, and deployment of advanced AI and generative AI-based products. You will drive technical innovation, lead complex projects, and collaborate closely with cross-functional teams to deliver high-quality, scalable, and maintainable solutions. This role requires a strong background in software development, AI/ML techniques, and DevOps practices, along with the ability to mentor junior engineers and contribute to strategic technical decisions.

Responsibilities

• Advanced Software Development: Design, develop, and optimize high-quality code for complex software applications and systems, maintaining high standards of performance, scalability, and maintainability. Drive best practices in code quality, documentation, and test coverage.
• GenAI Product Development: Lead end-to-end development of generative AI solutions, from data collection and model training to deployment and optimization. Experiment with cutting-edge generative AI techniques to enhance product capabilities and performance.
• Technical Leadership: Take ownership of architecture and technical decisions for AI/ML projects. Mentor junior engineers, review code for adherence to best practices, and ensure the team follows a high standard of technical excellence.
• Project Ownership: Lead execution and delivery of features, managing project scope, timelines, and priorities in collaboration with product managers. Proactively identify and mitigate risks to ensure successful, on-time project completion.
• Architectural Design: Contribute to the architectural design and planning of new features, ensuring solutions are scalable, reliable, and maintainable. Engage in technical reviews with peers and stakeholders, promoting a product suite mindset.
• Code Review & Best Practices: Conduct rigorous code reviews to ensure adherence to industry best practices in coding standards, maintainability, and performance optimization. Provide feedback that supports team growth and technical improvement.
• Testing & Quality Assurance: Design and implement robust test suites to ensure code quality and system reliability. Advocate for test automation and the use of CI/CD pipelines to streamline testing processes and maintain service health.
• Service Health & Reliability: Monitor and maintain the health of deployed services, utilizing telemetry and performance indicators to proactively address potential issues. Perform root cause analysis for incidents and drive preventive measures for improved system reliability.
• DevOps Ownership: Take end-to-end responsibility for features and services, working in a DevOps model to deploy and manage software in production. Ensure efficient incident response and maintain a high level of service availability.
• Documentation & Knowledge Sharing: Create and maintain thorough documentation for code, processes, and technical decisions. Contribute to knowledge sharing within the team, enabling continuous learning and improvement.
  
  

Minimum Qualifications

• Educational Background: Bachelor’s degree in Computer Science, Engineering, or a related technical field; Master’s degree preferred.
• Experience: 6+ years of professional software development experience, including significant experience with AI/ML or GenAI applications. Demonstrated expertise in building scalable, production-grade software solutions.
• Technical Expertise: Advanced proficiency in Python, FastAPI, PyTest, Celery, and other Python frameworks. Deep knowledge of software design patterns, object-oriented programming,and concurrency.
• Cloud & DevOps Proficiency: Extensive experience with cloud technologies (e.g., GCP,AWS, Azure), containerization (e.g., Docker, Kubernetes), and CI/CD practices. Strong understanding of version control systems (e.g., GitHub) and work tracking tools (e.g., JIRA).
• AI/GenAI Knowledge: Familiarity with GenAI frameworks (e.g., LangChain, LangGraph), MLOps, and AI lifecycle management. Experience with model deployment and monitoring in cloud environments.
  
  

Preferred Qualifications

• AI & Machine Learning: Hands-on experience with advanced ML algorithms, including generative models, NLP, and transformers. Knowledge of industry-standard AI frameworks (e.g.,TensorFlow, PyTorch) and experience with data preprocessing and model evaluation.
• Data & Analytics Tools: Proficiency with relational and NoSQL databases (e.g., MongoDB,MSSQL, PostgreSQL) and analytics platforms (e.g., BigQuery, Snowflake, Tableau). Experience with messaging systems (e.g., Kafka) is a plus.
• Testing & Quality: Experience with test automation tools (e.g., PyTest, xUnit) and CI/CD tooling such as Terraform and GitHub Actions. Strong emphasis on building resilient and testable software.
• Advanced Cloud Knowledge: Proficiency with GCP technologies such as VertexAI, BigQuery, GKE, GCS, and DataFlow, with a focus on deploying AI models at scale
  
  

Where we’re going

UKG is on the cusp of something truly special. Worldwide, we already hold the #1 market share position for workforce management and the #2 position for human capital management. Tens of millions of frontline workers start and end their days with our software, with billions of shifts managed annually through UKG solutions today. Yet it’s our AI-powered product portfolio designed to support customers of all sizes, industries, and geographies that will propel us into an even brighter tomorrow!

UKG is proud to be an equal opportunity employer and is committed to promoting diversity and inclusion in the workplace, including the recruitment process.     

Disability Accommodation 

For individuals with disabilities that need additional assistance at any point in the application and interview process, please email UKGCareers@ukg.com