Sr Engineer, Software - Enterprise Procurement and Planning Engineering Technology

Job Responsibilities

• Develop software solutions and conduct tests to drive engineering projects and ensure quality deliverables
• Contribute to design innovations that improve systems, processes, or services using new frameworks and industry best practices
• Collaborate with technical teams to deliver solutions and mentor others through knowledge sharing and training sessions
• Evaluate and apply current technologies that align with business goals
• Create clear documentation for software code, system designs, and business requirements to support knowledge sharing
• Evaluate, integrate, and maintain AI/ML capabilities — including LLM APIs, local model deployments, RAG pipelines, and MCP server integrations — to enhance platform intelligence and automation across procurement and supply chain workflows
• Apply AI-assisted development practices and contribute to responsible AI standards, including prompt engineering, output validation, and guardrails aligned with enterprise security and compliance requirements
• Support technology strategy by evaluating and applying current technologies that align with business goals
• Provide day-to-day BAU (Business-as-Usual) support for the Enterprise Procurement / STP platform
• Execute and support application deployments, configuration changes, and production support activities
• Support SAP Ariba administration, including user access management and operational configurations
• Develop and support integrations, APIs, and platform enhancements as required
• Assist in change request (CR) execution, defect resolution, and release readiness
• Partner with TPMs and SOX Control Operators to ensure secure, compliant operations
• Contribute to process improvements, documentation, and operational runbooks
• Participate in offshore/onshore collaboration with defined overlap hours

Education and Work Experience

• Bachelor's Degree plus 5 years of related work experience OR Advanced degree with 3 years of related experience (Required)
• Technical engineering experience using the .NET stack (ASP.NET Core / ASP.NET MVC / ASP.NET Web API / C#), front-end frameworks (e.g., Angular, Razor Pages or Blazor), Oracle SQL / MS SQL, Kubernetes, and API Gateway technologies
• Strong experience with Kubernetes, C#/.NET Core, Python, SQL, Splunk, Java-Spring Boot and Grafana.
• Deep expertise in microservices architecture and distributed systems.
• Hands-on experience with AI/ML integration patterns — including LLM APIs (OpenAI, Azure OpenAI, Anthropic), RAG pipelines, vector databases, and MCP server development — applied within .NET or Python backend systems
• Experience building production AI agents using LangChain, LangGraph, or AWS Bedrock Agents, including tool-use design, stateful multi-step reasoning, and integration with enterprise APIs and ERP workflows
• Familiarity with local model operations (Ollama, vLLM, fine-tuning with LoRA/QLoRA) and AI-augmented development practices including prompt engineering, output validation, and responsible AI guardrails in enterprise environments
• Hands-on experience with CI/CD pipelines (GitLab/GitHub), observability, and operational tooling.

Required Knowledge, Skills and Abilities

• Strong hands-on experience in software engineering, platform support, or enterprise application development
• Experience with procurement platforms, or ERP-adjacent systems
• API development and integration experience using Java and Python
• Experience supporting enterprise SaaS platforms or large-scale systems
• Working knowledge of AI/ML integration patterns — LLM APIs, RAG pipelines, vector databases, and MCP server connectivity — within enterprise .NET or Python environments
• AI agent design and orchestration (LangChain, LangGraph, AWS Bedrock Agents, or equivalent frameworks)
• Familiarity with AI-assisted development tooling (GitHub Copilot, Cursor, or similar) and responsible AI practices including prompt engineering, output validation, and compliance-aware guardrails
• Solid understanding of production support, deployments, and operational ownership
• Analytical Thinking, Analytics Collaboration, Communication, Customer Service, Mentorship Programming Languages, Software Design, Software Development, System Integration, Technical Writing