22 hours ago
Bethesda, MD, USASenior
Responsibilities
- Develop LLM-powered applications for retrieval, semantic search, summarization, document analysis, question answering, and decision support.
- Build and integrate RAG pipelines, embeddings, vector search, semantic retrieval, prompt orchestration, context management, evaluation, source citation, and output grounding.
- Develop Python-based APIs and AI application services for production environments.
- Implement guardrails, access controls, authentication, logging, monitoring, error handling, output validation, and traceability.
- 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.
- Create 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.
- Apply security, privacy, accessibility, data governance, and records-management requirements to AI applications.
Requirements
- 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, LLM evaluation, source citation, grounding, traceability, and output validation.
- Experience implementing AI guardrails, access controls, logging, monitoring, and error handling.
- Experience integrating AI or 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 are required.
- Active Top Secret clearance is highly preferred.
- Preferred qualifications include Federal financial or grants data experience, secure Federal/on-premises/cloud/hybrid deployment experience, open-source LLM and AI/ML framework experience, vector database or semantic search experience, Linux familiarity, PostgreSQL or Microsoft SQL Server familiarity, Kubernetes or Rancher experience, Jenkins or self-hosted Azure DevOps familiarity, Java or .NET integration experience, and knowledge of LLM observability, evaluation frameworks, prompt/version management, AI lifecycle management, AI security, model governance, responsible AI, and data protection.
Benefits
- Competitive compensation with opportunities for bonuses.
- Employer-paid health care.
- Training and development funds.
- 401k match.
Tech Stack
Categories
About Analytica
Analytica provides data and software engineering, analytics, and IT modernization consulting to U.S. government health, civilian, and national security agencies. Its services span cloud and enterprise data platforms (e.g., AWS, Databricks), DevSecOps, GIS, and AI/ML, delivered via government contracts. Founded in 2009 and headquartered in Washington, DC, the privately held firm is an SBA-certified 8(a) and HUBZone small business.