Key Responsibilities
Technical Leadership & Architecture
- Provide technical leadership and architecture for Generative and Agentic AI initiatives
- Design end-to-end AI system architectures covering orchestration, data, APIs, security, and deployment
- Build LLM-based solutions using RAG, embeddings, prompt engineering, function calling, and agentic workflows
- Ensure production readiness including CI/CD, testing, observability, scalability, security, and cost optimization
- Mentor AI engineers and collaborate with business and technology stakeholders
Generative & Agentic AI Engineering
- Design and build LLM-based systems using techniques such as:
- Retrieval Augmented Generation (RAG)
- Embeddings and vector search
- Prompt engineering and prompt optimization
- Function calling and tool usage
- Agentic and multi-agent workflows
- Build AI systems that integrate LLMs with APIs, data platforms, enterprise applications, and workflow engines
- Apply modern AI evaluation approaches including automated testing, benchmarking, and qualitative + quantitative LLM evaluation
Engineering Exc ellence & Operations
- · Apply strong software engineering and distributed systems principles to AI development
- · Design for observability, including logging, metrics, tracing, alerts, and model performance monitoring
- · Diagnose and resolve production issues related to latency, reliability, data quality, and model behavior
- · Balance innovation speed with operational excellence and long-term maintainability
Collaboration, Enablement & Mentorship
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