Job Purpose and Impact

• Experienced professional individual contributor who works independently on end-to-end delivery of production-grade AI Assistants, GenAI applications, data platforms, and automation solutions. Solves difficult, multi-component technical problems with limited supervision and may provide peer review or technical coaching within the job area.

  The Software Engineer will design, build, test, deploy, and support AI Assistants, AI Agents, and workflow automation solutions using ChatGPT-based copilots, Copilot Studio agents, Power Automate, and cloud-native services. Deliverables may span Python microservices, APIs and integration services, retrieval and vector-search pipelines, LLM/RAG/agent workflows, operational tooling, and user-facing experiences.

  Working within the Food APAC Digital Technology and Data team, this role will translate product requirements into secure, scalable, observable, and cost-efficient services or agents. The engineer will contribute across the full solution lifecycle—from experimentation and prototyping through production deployment, monitoring, support, and continuous improvement.

Key Accountabilities

• Design, Development & Support

  • Build reusable Agentic AI workflows and automate business processes.
  • Develop scalable Python microservices for LLM, RAG, and AI agent solutions.
  • Implement prompt engineering, vector search, retrieval pipelines, grounding, and caching.
  • Optimize AI solution performance, scalability, and cost.
  • Develop, test, debug, and maintain AI applications and services.
  • Create and maintain technical documentation and deployment guides.

  Operational Excellence

  • Develop runbooks, monitoring dashboards, alerts, and incident-response procedures.
  • Troubleshoot and resolve production issues to ensure reliability and uptime.

  Collaboration & Delivery

  • Partner with cross-functional teams to design and deliver business solutions.
  • Work in Agile environments with end-to-end ownership of solution delivery.
  • Ensure compliance with architecture, security, governance, privacy, and Responsible AI standards.

  Technology Exposure

  • Experience with Python, APIs, cloud platforms, CI/CD, containerization, RAG, vector databases, and monitoring tools.
  • Exposure to Salesforce, Service Cloud, CPQ, Salesloft, ChatGPT, Copilot Studio, Power Automate, or similar platforms is preferred.

Qualifications

• Minimum requirement of 3 years of experience building AI-based software solutions or data platforms.

  • Typically reflects 3 years or more of relevant experience, including 2+ years working with cloud-native AI/ML or GenAI systems on Azure, AWS, or GCP, or 2+ years of software development experience.