• Design & Build/Development & Support
• Develop multi-agent workflow automation patterns using Agentic AI
• Process redesign and mapping to agentic workflow patterns
• Architect scalable micro-services that wrap LLM/RAG/Agent workflows (Python).
• Implement robust prompt-engineering patterns, retrieval pipelines, and caching for AI Assistants and AI Agents
• Profile inference latency, GPU/CPU utilization, and memory
• Writes and maintains highly complex unit tests and integration tests, and performs debugging to maintain the quality and performance of the software/AI solutions
• Lead bug-fix, security-patch, and performance-tuning sprints for live AI Assistants and AI Agents
• Leads the establishment and maintenance of comprehensive documentation for agents, applications, deployment processes and system configurations.
• Collaboration & Leadership
  • Leads cross functional team of engineers to gather requirements and deliver solutions that meet business needs.
  • Experience working within product and agile delivery frameworks including backlog management and cross-functionality delivery and full E2E engineering.
  • Experience with enterprise architecture, data governance, or security standards in the context of digital solution delivery as part of E2E engineering and solution architecture.
• Capability & Technology Stack Exposure
  • Experience with digital technologies in the commercial & sales management capability (e.g. Salesforce, Service Cloud, CPQ, Salesloft, ChatGPT or similar platforms)

MINIMUM & TYPICAL YEARS OF WORK EXPERIENCE

• Minimum requirement of 4 years of relevant work experience. Typically reflects 5 years or more of relevant experience.
• Typically reflects 4 years or more with 3+ years of cloud-native AI/ML or GenAI systems (Azure, AWS, or GCP)