Software Engineer - CRS

Agilysys, Inc.
7d

About The Position

We are looking for a Software Engineer to help design and deliver intelligent, data-driven solutions that enhance our platform and customer experience. In this role, you will build and deploy AI-powered capabilities—from predictive models to generative AI applications—while partnering closely with product, data, and engineering teams to bring innovative ideas into production.

Requirements

  • Bachelor’s degree in Computer Science, Software Engineering, Data Science, or a related technical field (or equivalent practical experience)
  • 1 - 3 years of software engineering experience, with 1+ years working on AI/ML systems
  • Experience deploying ML or AI models into production environments
  • Hands-on experience with generative AI and LLM-based applications
  • Proficiency in .Net and at least one additional language (e.g., Java, C#, or JavaScript)
  • Experience with ML frameworks (TensorFlow, PyTorch, or similar)
  • Familiarity with LLM tooling (e.g., OpenAI APIs, LangChain, vector databases, prompt engineering)
  • Experience with Azure cloud platforms and scalable infrastructure
  • Knowledge of data engineering concepts and tools (ETL pipelines, data lakes, etc.)
  • Strong problem-solving and system design skills
  • Ability to translate ambiguous business problems into AI-driven solutions
  • Strong communication and collaboration skills

Nice To Haves

  • Experience building AI features for SaaS platforms or customer-facing applications
  • Knowledge of recommendation systems, NLP, or personalization engines
  • Experience with real-time data processing and event-driven architectures
  • Familiarity with responsible AI practices, data privacy, and model governance

Responsibilities

  • Design, build, and deploy machine learning and AI-powered features into production systems
  • Develop and integrate generative AI applications (e.g., LLM-powered copilots, chat interfaces, automation tools)
  • Implement data pipelines to support model training, inference, and monitoring
  • Architect scalable AI/ML systems within a cloud-native environment
  • Optimize model performance, latency, and cost for real-world production use
  • Ensure robust APIs and services for integrating AI capabilities into core products
  • Support end-to-end ML lifecycle: data preparation, training, evaluation, deployment, and monitoring
  • Implement MLOps best practices, including versioning, retraining, and observability
  • Monitor model drift, performance degradation, and reliability in production
  • Partner with Product and business stakeholders to identify high-impact AI use cases
  • Mentor engineers and contribute to AI/ML best practices across the team
  • Collaborate with cross-functional teams to align AI capabilities with broader platform strategy

Benefits

  • Shape the next generation of AI-driven capabilities in hospitality technology
  • Work on high-impact, customer-facing innovations
  • Collaborate with a forward-thinking, global engineering team
  • Competitive compensation, benefits, and growth opportunities
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