Software Engr II

Honeywell Honeywell · Industrial · Bengaluru, Karnataka, India

Software Engineer with 3+ years of experience in .Net and Angular, responsible for designing, implementing, testing, and debugging complex software solutions. The role involves mentoring junior colleagues, managing end-to-end processes, and collaborating with cross-functional teams. Requires proficiency in C#, Angular, SQL, and experience with AI-assisted development tools and consuming AI/ML APIs.

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
  • web api
  • sql
  • C#
  • NoSQL databases
  • Software Development Life Cycle
  • AI-assisted development tools
  • AI-powered code analysis
  • LLM-based application capabilities
  • prompting
  • fine-tuning
  • AI/ML-powered APIs
  • Azure AI Services
  • Cognitive Services
  • OpenAI APIs
  • problem-solving
  • engineering principles
  • communication skills
  • 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,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).