Opportunity Description
What You'll Do
- Build GenAI applications leveraging foundation models and advanced architectures such as GraphRAG.
- Develop autonomous AI agents using modern agentic frameworks.
- Design and deploy RAG and GenAI services using Python (FastAPI), Docker, and cloud platforms (AWS, Azure, or GCP).
- Build scalable REST APIs that power LLM-driven applications integrated with enterprise data sources.
- Implement LLM evaluation frameworks using tools such as Ragas, LangSmith, or custom benchmarks to measure answer relevance, groundedness, and hallucination rates.
- Apply LLMOps/MLOps practices, including CI/CD pipelines, prompt/version management, automated testing, and monitoring of latency, cost, and response quality.
- Develop systems leveraging embeddings at scale, knowledge graphs, and ontology extraction.
- Collaborate across engineering teams, mentor developers, and help d...
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