Note: The job is a remote job and is open to candidates in USA. Electric Power Research Institute (EPRI) is seeking a Lead AI Engineer to design, implement, and support AI-driven document processing and search solutions. The role involves architecting AI systems, optimizing document retrieval, and collaborating with stakeholders to enhance AI-powered document solutions.

Responsibilities

• Architect & Deploy AI Solutions: Build AI-driven search and document intelligence systems using Azure AI Search, Knowledge Graphs, and RAG techniques
• Query Orchestration: Develop strategies to route and structure user queries efficiently across multiple retrieval systems
• RAG-Based Applications: Implement and fine-tune applications for intelligent knowledge retrieval from structured and unstructured documents
• Containerized Deployments: Deploy and manage AI applications using Azure Kubernetes Service (AKS) for scalability
• Vector Search Optimization: Enhance document retrieval through optimized embeddings and hybrid search techniques
• Open-Source Integration: Utilize tools like Tesseract OCR, PyMuPDF, and Pillow for document processing
• API Integration: Connect with Profile APIs, Product Metadata, and Downloads to enrich indexing and search capabilities
• Compliance & Security: Ensure adherence to export control restrictions and secure document handling best practices
• Monitoring & Optimization: Troubleshoot and optimize AI-based workflows for performance and reliability
• Stakeholder Collaboration: Work closely with business and technical teams to refine AI-powered document solutions

Skills

• Bachelors or Masters Degree in Computer Science or related areas, applicable professional certification with 7+ years of progressive experience providing solutions to complex program/system problems in a business environment
• 5+ years in AI/ML, cloud-based search, and document processing
• Expertise in Query Orchestration for complex AI pipelines
• Strong knowledge of RAG architectures for AI-powered search
• Hands-on experience with Azure AI Search, Document Intelligence, and Cognitive Services
• Proficiency in vector search, embeddings, and hybrid retrieval techniques
• Experience with Kubernetes (AKS) and containerized deployments
• Familiarity with Tesseract OCR, PyMuPDF, and Pillow
• Strong Python development skills for AI pipelines
• Experience with hybrid cloud AI solutions (on-prem + cloud)
• Familiarity with Azure OpenAI, LangChain, or AI Foundry
• Deep knowledge of multi-index query orchestration
• Expertise in Azure AI search semantic and vector profiling
• Expertise in vector other databases such as (FAISS, Weaviate, Pinecone)
• Background in NLP, document classification, and entity extraction
• Understanding of export control compliance and secure document handling

Benefits

• Medical
• Dental
• Vision
• 401k
• STD/LTD
• Paid family leave
• Life and accident insurance
• Paid time off (flexible vacation, sick leave, and holiday pay)

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