Our Client operates in the Food and Beverage Manufacturing Industry, with its headquarters rooted strongly in the United States. It has its branches spread to more than 70 countries, providing employment to more than 1,60,000 people all over the world. They fall in the Top 10 Largest Agricultural Companies in the World 2020. Their core business is to connect producers and users with agricultural needs, around the world, and also offer risk management solutions and other services for farmers.
Responsibilities:
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.
Operational Excellence
- Own on-call runbooks, SLOs, and incident reviews; embed observability
- Leads and mentors technical support and troubleshooting for highly complex issues with deployed applications to ensure minimal downtime and fast resolution.
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)
Requirements:
- 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) or 2+ years of software development.