Role Description The student will support the development of applications using low-code/no-code platforms, as well as traditional development when needed. Responsibilities include: - Assisting with the design, development, and testing of applications - Contributing to automation solutions - Improving functionality across projects Qualifications - Be eligible to get a secret clearance - Students pursuing degrees in Computer Science, Software Engineering, Computer Engineering, or related field - AI knowledge Requirements - Certifications in AWS (preferred) Benefits - Part Time Position: 10 hours per week - Location: 100% Remote Company Description N2IA Technologies is a consulting company specializing in acquisition/contracting support, cost/FinOps, and technology optimization for federal clients. We deliver tailored strategies, robust software solutions, and streamlined operations to help organizations achieve their goals. At N2IA, we are committed to developing innovative financial and compliance-based solutions that address evolving business and regulatory needs.

Role Description The Lead AI Engineer is to design, implement, and support AI-driven document processing, retrieval, and search solutions using Azure AI Search, Retrieval-Augmented Generation (RAG), Knowledge Graphs, Query Orchestration, Prompt Engineering, and Kubernetes-based container deployments. Key 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. Qualifications - 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. Specialized Expertise - Search & RAG: Semantic, BM25, similar ranking and vector search optimization. - Custom scoring profiles and relevance tuning. - Evaluation metrics (nDCG, MRR, precision@k). - Query rewriting, synonym maps, and semantic expansion. - Integration with RAG and LLM pipelines for optimized context retrieval. Prompt Engineering - Systematic prompt design and evaluation. - RAG-oriented prompting with grounding and guardrails. - Instruction hierarchies and multi-agent orchestration. - Domain adaptation for EPRI’s technical language. - Continuous improvement through telemetry and quality analysis. Preferred Qualifications - 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 databases such as FAISS, Weaviate, Pinecone. - Background in NLP, document classification, and entity extraction. - Understanding of export control compliance and secure document handling. Salary and Benefits - The salary range for this position is $145,000 USD to $175,000 USD annually. - This salary range is an estimate, and the actual salary may vary based on various factors, including education, experience, skills, and abilities. - This role is eligible to participate in EPRI’s annual incentive program. - This role is eligible to participate in EPRI’s standard employee benefit programs, which currently include medical, dental, vision, 401k, STD/LTD, paid family leave, life and accident insurance, and paid time off (flexible vacation, sick leave, and holiday pay). Company Description EPRI participates in E-Verify, an online system operated jointly by the Department of Homeland Security and the Social Security Administration (SSA). EPRI uses the system to check the work status of new hires by comparing information from the employee's I-9 form against SSA and Department of Homeland Security databases. EPRI is an equal opportunity employer. EEO/AA/M/F/VETS/Disabled. Together . . . Shaping the Future of Energy. www.epri.com

• Identify and automate manual workflows using AI tools and process optimization techniques • Analyze business and operational data to identify trends, performance gaps, and insights • Develop prompts, automation workflows, and AI-assisted solutions for business use cases • Support cross-functional projects across AI, Product, Operations, and Revenue Cycle teams • Break down ambiguous business problems into structured analyses and actionable solutions • Translate data insights into clear, business-facing recommendations • Participate in pilot programs and innovation initiatives focused on efficiency and transformation • Document processes, best practices, and repeatable AI-enabled workflows • Maintain strong execution discipline with proactive communication on progress, risks, and blockers • Utilize AI tools as part of daily workflow for research, analysis, and automation • Develop proficiency in prompt engineering, automation, and AI-assisted analytics • Continuously assess emerging AI tools and recommend practical use cases • Contribute to internal AI capability building and knowledge sharing

Role Description Choosing Capgemini means choosing a place where you'll be empowered to shape your career, supported by a collaborative global community, and inspired to reimagine what's possible. Join us in helping enterprises unlock the value of Artificial Intelligence and drive intelligent business transformation at scale. In this role, you will: - Ability to lead AI solution architecture, client engagements, and AI transformation initiatives. - Strong expertise in Generative AI, LLMs (GPT, Claude, Gemini, Llama), and Prompt Engineering. - Hands-on experience building Agentic AI and Multi-Agent Systems using CrewAI, AutoGen, LangGraph, or Semantic Kernel. - Proficiency in Python, FastAPI, REST APIs, and Microservices architecture. - Strong knowledge of RAG, Vector Databases, Embeddings, and Enterprise Knowledge Systems. - Experience with Azure OpenAI, Azure AI Services, AWS Bedrock, and cloud-based AI platforms. - Understanding of AI governance, observability, security, and responsible AI practices. Benefits - We value flexibility and support our employees with remote work options and adaptable schedules to maintain a healthy work-life balance. - Our inclusive culture brings together diverse professionals committed to growth, innovation, and excellence. - You'll have access to continuous learning opportunities and certifications in emerging technologies such as Artificial Intelligence, Generative AI, Cloud, Data, and Enterprise Architecture.