Software Engr II

Honeywell Honeywell · Industrial · Bengaluru, Karnataka, India

Software Engineer with full-stack .Net and Angular experience, focusing on designing, implementing, and testing scalable applications. The role involves database management, cross-functional collaboration, and staying updated with industry trends. A key aspect is the use and integration of AI-assisted development tools and AI/ML-powered APIs, indicating an exploratory engagement with AI technologies within a traditional software engineering context.

What you'd actually do

  1. Design and implement robust, scalable, and maintainable applications using .NET for the backend and Angular for the frontend.
  2. Extensive hands-on experience in database management including proficiency in SQL and NoSQL databases.
  3. Write clean, efficient, and well-documented code, following best practices and coding standards, testing methodologies, and deployment processes.
  4. Conduct thorough testing and debugging of applications to ensure high performance and reliability.
  5. Work closely with cross-functional teams, including product managers, Architects, designers, and QA engineers, to deliver integrated solutions.

Skills

Required

  • .Net
  • Angular
  • SQL
  • NoSQL
  • C#
  • web api
  • Software Development Life Cycle
  • AI-assisted development tools
  • AI-powered code analysis
  • LLM-based application capabilities
  • AI/ML-powered APIs
  • problem-solving
  • communication
  • interpersonal skills
  • Agile development methodologies
  • cyber security
  • secure coding practices

Nice to have

  • design patterns
  • solid principles

What the JD emphasized

  • Minimum of 3 years of experience in .Net and Angular, Angular, web api, sql
  • Strong proficiency in C# , Angular and Database following Software Development Life Cycle
  • Experience using AI-assisted development tools (e.g., GitHub Copilot, Visual Studio IntelliCode, code-generation tools) to enhance productivity.
  • Understanding of AI-powered code analysis, refactoring, and optimization recommendations.
  • Basic understanding of LLM-based application capabilities, including prompting, fine-tuning, and constraints.
  • Ability to integrate or consume AI/ML-powered APIs (e.g., Azure AI Services, Cognitive Services, OpenAI APIs).