We are seeking an experienced
Senior AI Engineer to build retrieval, semantic search, summarization, and source-traceable AI application capabilities for a Federal data analytics and AI modernization initiative.
The team will deliver a secure, scalable platform that integrates structured and unstructured data, provides data visualization and traceable AI-assisted analytics, and gives examiners centralized tools for search, review, monitoring, and decision support. The platform will support professional judgment and will not replace authoritative agency financial or grants-management systems or execute financial transactions.
We offer competitive compensation with opportunities for bonuses, employer paid health care, training and development funds, and 401k match.
Key Responsibilities- Develop LLM-powered applications for retrieval, semantic search, summarization, document analysis, and decision support.
- Build and integrate RAG pipelines, embeddings, vector search, and semantic retrieval capabilities.
- Develop Python-based APIs and AI application services for production environments.
- Implement prompt orchestration, context management, evaluation, source citation, and output grounding.
- Implement guardrails, access controls, authentication, logging, error handling, and output validation.
- Evaluate and optimize AI applications for accuracy, relevance, groundedness, latency, and reliability.
- Integrate AI services with databases, search platforms, APIs, and existing data pipelines.
- Troubleshoot and optimize LLM, retrieval, API, and AI application workflows.
- Develop technical documentation for AI architecture, retrieval workflows, APIs, evaluation methods, and operational procedures.
- Collaborate with AI/ML, data engineering, data science, and software engineering teams throughout development and testing.
- Apply security, privacy, accessibility, data governance, and records-management requirements to AI applications.
Required Qualifications- Hands-on experience developing applications using LLMs, RAG, semantic search, or generative AI.
- Experience building AI services for search, summarization, document analysis, question answering, or decision support.
- Strong Python and API development skills.
- Experience with embeddings, vector search, retrieval, prompt orchestration, and LLM evaluation.
- Experience implementing source citation, grounding, traceability, and output validation.
- Experience implementing AI guardrails, access controls, logging, monitoring, and error handling.
- Experience integrating AI/LLM services with databases, APIs, search platforms, and data pipelines.
- Strong technical communication, documentation, problem-solving, and cross-functional collaboration skills.
- U.S. citizenship and ability to obtain and maintain Top Secret eligibility.
- Active Top Secret clearance highly preferred.
Preferred Qualifications- Experience developing AI/LLM solutions for Federal financial, grants, budget, payment, award oversight, or financial reporting data.
- Experience deploying AI applications in secure Federal, on-premises, cloud, or hybrid environments.
- Experience with open-source LLMs and AI/ML frameworks.
- Experience with vector databases, semantic search engines, or hybrid search architectures.
- Experience with Linux.
- Familiarity with PostgreSQL and/or Microsoft SQL Server.
- Experience with Kubernetes and/or Rancher.
- Familiarity with Jenkins, self-hosted Azure DevOps, and CI/CD pipelines.
- Familiarity with Java and/or .NET applications and API integrations.
- Experience with LLM observability, evaluation frameworks, prompt/version management, and AI application lifecycle management.
- Familiarity with AI security, model governance, responsible AI, and data protection practices.
