Position Overview
Builds secure, production-ready generative-AI applications using large language models, retrieval-augmented generation, vector search, prompt engineering, evaluation, and guardrails.
Key Responsibilities
- Design and implement RAG workflows, including document ingestion, chunking, embedding, vector indexing, retrieval, prompt construction, and response generation.
- Integrate LLMs and foundation models through Azure OpenAI, AWS Bedrock, Vertex AI, OpenAI-compatible APIs, or approved alternatives.
- Develop prompts, system instructions, evaluation datasets, output-quality metrics, and test automation.
- Implement guardrails for content filtering, data leakage prevention, prompt-injection resistance, access enforcement, hallucination mitigation, and harmful-output controls.
- Integrate GenAI solutions with agency data sources, repositories, workflow tools, knowledge bases, APIs, and user interfaces.
- Implement observability for model usage, latency, failures, token consumption, quality signals, security events, and user feedback.
Minimum Qualifications
4+ years in software engineering, data engineering, AI/ML, NLP, or cloud application development. Demonstrated experience with LLMs, embeddings, vector databases, RAG architecture, APIs, Python or TypeScript/JavaScript, AI security, privacy, and evaluation practices preferred.
About This Opportunity
This is a full-time remote position supporting current and upcoming LaTronic Solutions client work. Specific client requirements, schedules, security requirements, clearances, and other project details may vary by engagement.
LaTronic Solutions is committed to a professional and inclusive workplace. Employment decisions are based on qualifications, merit, business need, and the requirements of the applicable engagement.
