Software Engineer, Senior
Summary
Senior full-stack engineer on Infor's Platform Engineering team, owning technical design and delivery of scalable services and front-end features using Python, C#, Angular, and AWS, while building AI/LLM-powered capabilities and contributing to AI Governance (explainability, observability, guardrails) and mentoring other engineers.
- Design, develop, and maintain production-grade services using Python, C#, and related technologies.
- Build and enhance front-end applications using Angular.
- Develop and integrate cloud-native solutions leveraging AWS services such as Bedrock, SageMaker, Lambda, and EKS.
- Implement AI and LLM-powered capabilities using Anthropic Claude API, Model Context Protocol (MCP), and related platforms.
- Contribute to AI Governance initiatives, including explainability, observability, and guardrail capabilities.
- Lead feature and component design, recommending implementation approaches and evaluating technical trade-offs.
- Collaborate with cross-functional teams to deliver scalable and reliable software solutions.
- Mentor engineers, conduct code reviews, and promote engineering best practices.
- Participate in technical planning, estimation, and architectural discussions.
- Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
- Strong experience developing and delivering production software applications.
- Proficiency in Python and working knowledge of C#.
- Experience with PostgreSQL or other relational databases.
- Strong full-stack development experience, including Angular.
- Experience working with AWS services such as Bedrock, SageMaker, Lambda, and EKS.
- Hands-on experience using AI-assisted development tools such as Claude Code, AWS Kiro, OpenAI Codex, or similar technologies.
- Experience building solutions using LangChain, LangGraph, or comparable agentic AI frameworks.
- Ability to design technical solutions from problem statements and drive implementation independently.
- Strong understanding of AI fundamentals, responsible AI usage, and evaluation of AI-generated outputs.
- Experience working with Anthropic Claude API and Model Context Protocol (MCP).
- Experience developing AI-powered products, services, or APIs.
- Knowledge of AI governance, explainability, observability, and safety/guardrail frameworks.
- Experience designing and delivering LLM-enabled applications in production environments.
- Proven ability to lead technical discussions, evaluate architectural trade-offs, and influence engineering decisions.
- Experience mentoring software engineers and reviewing technical designs.
- Strong communication and stakeholder collaboration skills.