Gen AI Engineer

Job Title: Gen AI Engineer

Location: Atlanta GA

Duration: 6 months

Term: Contract

Job Description:

Experience Desired: 7 Years.

Required Skills & Experience:

• Semantic Search & LLM Platforms Job Summary We are looking for a Generative AI Engineer to design build and scale an enterprise AI-powered semantic search platform for API discovery and knowledge retrieval.
• The role focuses on developing LLM-driven search RAG pipelines and cloud-native AI services that enable natural language interaction with large-scale technical repositories.
• The ideal candidate has strong hands-on experience with LLMs embeddings vector databases FastAPI microservices and multi-cloud AI deployments and is passionate about building reliable production-grade GenAI systems.

Key Responsibilities

• Design and implement AI-powered semantic search solutions for large-scale API and technical documentation repositories.
• Develop Retrieval-Augmented Generation (RAG) pipelines using OpenAI embeddings LangChain LangGraph and vector databases (FAISS pgvector).
• Build and maintain FastAPI-based microservices for LLM-powered search summarization and inference with secure authentication (JWT).
• Create and manage data ingestion and indexing pipelines including document chunking metadata extraction embedding generation and vector refresh workflows. Implement multi-cloud LLM integration and routing across Azure OpenAI AWS Bedrock and GPT-4 with fault-tolerant fallback mechanisms.
• Apply grounding techniques and hallucination mitigation strategies to improve response accuracy and reliability.
• Define and track RAG and LLM evaluation metrics such as precisionk grounding score latency and hallucination rate. Integrate monitoring logging and observability using LangSmith and OpenTelemetry for model performance and system health.
• Deploy and scale AI services using cloud-native architectures (AWS Lambda ECS Fargate API Gateway DynamoDB S3).
• Collaborate with UI/UX and platform teams to deliver intuitive interfaces for natural-language API discovery.
• Contribute to CI/CD pipelines to enable automated testing deployment and versioning of AI services.

Key Skills:

Machine Learning Multi-cloud ai Deployments semantic search llms Embeddings Vector databases.