Description

Responsibilities & Qualifications

Build GenAI applications leveraging foundation models and advanced architectures such as GraphRAG

Develop autonomous AI agents using modern agentic frameworks

Design and deploy RAG-based services using Python (FastAPI), Docker, and cloud platforms

Build scalable REST APIs powering LLM-driven applications integrated with enterprise data sources

Implement LLM evaluation frameworks using tools such as Ragas, LangSmith, or custom benchmarks

Apply LLMOps/MLOps practices including CI/CD pipelines, prompt management, automated testing, and monitoring

Develop systems leveraging embeddings, knowledge graphs, and ontology extraction

Collaborate with engineering teams and contribute to advanced GraphRAG and agentic AI architectures

Requirements

Degree in Computer Science, AI/ML, or related field

5+ years of AI/ML-focused software engineering experience

Production experience building LLM-based or agentic AI systems

Strong expertise in Python and modern AI frameworks

Experience with RAG / GraphRAG implementations and embeddings at scale

Experience deploying AI workloads to AWS, Azure, or GCP

Familiarity with LLMOps/MLOps tooling and model evaluation frameworks

Strong problem-solving, communication, and collaboration skills

Key Skills

Education

Bachelor's degree