Note: The job is a remote job and is open to candidates in USA. STAFFXPERT LLC is seeking an AI Engineer for its client to develop production-grade Generative AI solutions. The role focuses on agentic AI, GraphRAG, LLM applications, AI deployment, evaluation, LLMOps, and integration with enterprise platforms while mentoring engineers and evaluating emerging technologies.
Responsibilities
- Design, build, and deploy production-grade GenAI applications using foundation models and advanced architectures such as GraphRAG
- Develop autonomous AI agents using frameworks such as Google ADK, LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar technologies
- Take GenAI solutions from proof of concept through production while ensuring scalability, reliability, observability, and maintainability
- Design and implement RAG and GraphRAG pipelines using embeddings, vector databases, knowledge graphs, and enterprise data sources
- Develop scalable REST APIs using Python and FastAPI
- Containerize and deploy AI services using Docker and cloud platforms such as AWS, Azure, or Google Cloud Platform
- Implement LLM evaluation frameworks to measure response quality, groundedness, latency, and hallucination rates
- Apply LLMOps practices including CI/CD, prompt and model version management, automated testing, monitoring, and observability
- Collaborate with engineering teams to integrate AI capabilities into enterprise platforms
- Mentor engineers and contribute to GenAI development standards and best practices
- Evaluate emerging GenAI technologies, agent frameworks, and industry trends
Skills
- Bachelor's degree in Computer Science or a related technical field, or equivalent practical experience
- 5+ years of software engineering experience, including recent experience developing GenAI or LLM-powered applications
- Proven experience taking GenAI applications from proof of concept to production
- Hands-on experience with modern agent development frameworks such as Google ADK, LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar
- Strong Python development skills, including FastAPI and REST API development
- Experience implementing RAG or GraphRAG solutions
- Experience with embeddings, vector databases, knowledge graphs, and enterprise data integration
- Experience deploying AI workloads using Docker and AWS, Azure, or Google Cloud Platform
- Familiarity with LLMOps practices, including CI/CD, prompt management, model governance, monitoring, and evaluation
- Experience with LLM evaluation tools such as LangSmith, Ragas, DeepEval, or equivalent
- Strong communication, collaboration, analytical, and problem-solving skills
- Experience building enterprise-scale AI platforms and applications
- Experience with production observability and AI application monitoring
- Strong understanding of emerging agentic AI architectures and multi-agent systems
- Demonstrated ability to evaluate and adopt emerging GenAI technologies
Company Overview
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