AI Engineer / Search Engineer

Certified Technical Experts, Inc.; Peachtree Corners (GA); On-site; USD 96,000 - 100,000; Full time

Job summary

Certified Technical Experts, Inc. is seeking an AI Engineer / Search Engineer to support FLRA’s Intelligent Document Processing and AI-Enabled Search initiative.

This onsite role in Peachtree Corners, GA, will design, implement, tune, test, and support AI-powered search and question answering components within a Microsoft 365 GCC/Azure environment. The work centers on semantic and vector retrieval, Retrieval-Augmented Generation (RAG), document classification, and source-grounded responses that

Qualifications

• 5+ years of software, search, AI, ML, or data engineering experience.
• 3+ years of hands-on enterprise search, AI/ML, or cloud-based AI solutions.
• Strong hands-on experience with Azure AI Search or comparable enterprise search technology.
• Experience with semantic search, vector search, embeddings, similarity search, and relevance ranking.
• Experience implementing Retrieval-Augmented Generation (RAG) solutions.
• Experience with Azure OpenAI, OpenAI APIs, or comparable large-language-model platforms.
• Experience developing source-grounded question-answering solutions.
• Strong experience with Python, C#/.NET, or similar programming languages.
• Experience with Azure AI Document Intelligence or comparable OCR/document-processing technology.
• Experience with document classification and structured metadata extraction.
• Experience working with unstructured content such as PDFs, scanned documents, and OCR-generated text.

Responsibilities

• Design and implement AI-enabled search capabilities for FLRA’s bargaining unit records.
• Configure and optimize Azure AI Search indexes, including fields, filters, analyzers, semantic configurations, and vector search.
• Build and support multiple search modalities such as keyword, Boolean, full-text, metadata, semantic, and vector-based search.
• Develop and support natural-language question answering and source-grounded responses using Azure OpenAI or other approved AI services.
• Implement RAG patterns using FLRA documents, extracted metadata, and search indexes.
• Generate, store, and manage embeddings for semantic and vector retrieval.
• Ensure AI-generated responses cite or reference the originating Government documents.
• Support document classification, metadata extraction, and confidence scoring using Azure AI Document Intelligence and related AI capabilities.
• Develop logic to identify and maintain relationships among bargaining unit records, including amendments, consolidations, reorganizations, revocations, successorship determinations, and related cases.
• Develop and tune relevance-ranking strategies to improve search accuracy and usability.
• Configure metadata filters and structured retrieval using FLRA-required fields such as agency, bargaining unit, labor organization, case number, docket number, certification type, dates, region, and location.
• Support human-in-the-loop validation workflows for reviewing AI-generated classifications and metadata.
• Develop evaluation methods for search quality, retrieval relevance, classification accuracy, metadata extraction, and AI response quality.
• Tune prompts, retrieval strategies, chunking approaches, embeddings, and search configurations based on testing and Government feedback.
• Implement guardrails so AI responses remain grounded in authorized FLRA content and do not generate unsupported information.
• Support automated ingestion and indexing of newly received documents.
• Collaborate with the Azure Platform & Integration Engineer to integrate AI/search services with SharePoint, APIs, Azure services, and application components.
• Participate in system integration testing, UAT, defect resolution, production deployment, monitoring, and performance tuning.
• Maintain technical documentation covering AI models, prompts, search configurations, index schemas, evaluation methods, and operational procedures.
• Follow Federal security requirements, including CUI protection, FedRAMP-authorized services, least-privilege access, and NIST SP 800-53 controls.

Skills

Python

C#/.NET

Azure AI Search

Azure OpenAI

RAG

Semantic search

Vector search

Search relevance tuning

REST APIs

Git CI/CD

Documentation

Stakeholder comms

Education

Bachelor’s degree in Computer Science, AI, Data Science, or related field

Tools

Azure OpenAI

Azure AI Document Intelligence

SharePoint

Microsoft Graph API

MS 365 environments

Job description

Certified Technical Experts, Inc. is seeking an AI Engineer / Search Engineer to support FLRA’s Intelligent Document Processing and AI-Enabled Search initiative. In this onsite role in Peachtree Corners, GA, you will design, implement, tune, test, and support AI-powered search and question answering components within an approved Microsoft 365 GCC/Azure environment.

The work centers on semantic and vector retrieval, Retrieval-Augmented Generation (RAG), document classification, and source-grounded responses that cite the underlying Government documents. You will also collaborate on system integration, evaluation, and production readiness while meeting Federal security requirements.

Key Responsibilities

• Design and implement AI-enabled search capabilities for FLRA’s bargaining unit records.
• Configure and optimize Azure AI Search indexes, including fields, filters, analyzers, semantic configurations, and vector search.
• Build and support multiple search modalities such as keyword, Boolean, full-text, metadata, semantic, and vector-based search.
• Develop and support natural-language question answering and source-grounded responses using Azure OpenAI or other approved AI services.
• Implement RAG patterns using FLRA documents, extracted metadata, and search indexes.
• Generate, store, and manage embeddings for semantic and vector retrieval.
• Ensure AI-generated responses cite or reference the originating Government documents.
• Support document classification, metadata extraction, and confidence scoring using Azure AI Document Intelligence and related AI capabilities.
• Develop logic to identify and maintain relationships among bargaining unit records, including amendments, consolidations, reorganizations, revocations, successorship determinations, and related cases.
• Develop and tune relevance-ranking strategies to improve search accuracy and usability.
• Configure metadata filters and structured retrieval using FLRA-required fields such as agency, bargaining unit, labor organization, case number, docket number, certification type, dates, region, and location.
• Support human-in-the-loop validation workflows for reviewing AI-generated classifications and metadata.
• Develop evaluation methods for search quality, retrieval relevance, classification accuracy, metadata extraction, and AI response quality.
• Tune prompts, retrieval strategies, chunking approaches, embeddings, and search configurations based on testing and Government feedback.
• Implement guardrails so AI responses remain grounded in authorized FLRA content and do not generate unsupported information.
• Support automated ingestion and indexing of newly received documents.
• Collaborate with the Azure Platform & Integration Engineer to integrate AI/search services with SharePoint, APIs, Azure services, and application components.
• Participate in system integration testing, UAT, defect resolution, production deployment, monitoring, and performance tuning.
• Maintain technical documentation covering AI models, prompts, search configurations, index schemas, evaluation methods, and operational procedures.
• Follow Federal security requirements, including CUI protection, FedRAMP-authorized services, least-privilege access, and NIST SP 800-53 controls.

Required Qualifications

• Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, Information Technology, or related field, or equivalent professional experience.
• 5+ years of software, search, AI, machine learning, or data engineering experience.
• 3+ years of hands-on experience with enterprise search, AI/ML, or cloud-based AI solutions.
• Strong hands-on experience with Azure AI Search or comparable enterprise search technology.
• Experience with semantic search, vector search, embeddings, similarity search, and relevance ranking.
• Experience implementing Retrieval-Augmented Generation (RAG) solutions.
• Experience with Azure OpenAI, OpenAI APIs, or comparable large-language-model platforms.
• Experience developing source-grounded question-answering solutions.
• Strong experience with Python, C#/.NET, or similar programming languages.
• Experience with Azure AI Document Intelligence or comparable OCR/document-processing technology.
• Experience with document classification and structured metadata extraction.
• Experience working with unstructured content such as PDFs, scanned documents, and OCR-generated text.
• Experience designing search index schemas, metadata models, filters, and query strategies.
• Experience with text chunking, embedding generation, vector indexing, and retrieval strategies.
• Experience with prompt engineering and LLM integration.
• Experience evaluating and tuning search relevance and AI-generated responses.
• Understanding of hallucination mitigation, grounding, citations, confidence scoring, and responsible AI practices.
• Experience integrating AI/search services with REST APIs, Azure services, or enterprise applications.
• Familiarity with Microsoft SharePoint, Microsoft Graph API, and Microsoft 365 environments.
• Experience with Git-based source control, CI/CD, testing, and deployment practices.
• Understanding of secure cloud development, identity management, and least-privilege access.
• Strong analytical, troubleshooting, communication, and technical documentation skills.
• Ability to work closely with team and Government stakeholders.
• Ability to successfully complete required FLRA personnel security vetting.

Salary and Location

• Location: Peachtree Corners, GA (onsite)
• Compensation: USD 96,100 - 100,000 per year

Technology Focus

• Azure AI Search
• Azure OpenAI
• Azure AI Document Intelligence
• Embeddings
• Retrieval-Augmented Generation (RAG)
• Natural-language question answering
• Vector search
• Semantic search
• Python
• C#/.NET
• OpenAI APIs
• Microsoft SharePoint
• Microsoft Graph API
• Microsoft 365
• REST APIs
• Git-based source control
• CI/CD
• FedRAMP
• NIST SP 800-53

Preferred Certifications

• Microsoft Certified: Azure AI Engineer Associate
• Microsoft Certified: Azure Data Scientist Associate
• Microsoft Certified: Azure Developer Associate
• Microsoft Certified: Azure Solutions Architect Expert
• Microsoft Certified: Azure Data Engineer Associate
• Microsoft Applied Skills related to Azure AI Search, Azure OpenAI, or generative AI
• CompTIA Security+ or equivalent security certification