[Remote] Lead Search and AI Engineer
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)
Company Overview
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