> Markdown version of [/jobs/ext/3657901-ai-engineer](https://www.wearedevelopers.com/jobs/ext/3657901-ai-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Engineer - **Company:** Integrated Document Solutions Inc. - **Location:** Miami, FL, United States - **Experience:** Experienced - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Data Analysis, VoIP, Databases, Image Analysis, System Configuration, Data Architecture, Information Engineering, Data Integration, Extract Transform Load (ETL), Data Transformation, Data Security, Data Warehousing, Database Queries, Dimensional Modeling, Health Information Technology, Python (Programming Language), Microsoft SQL Server, Natural Language Processing, Performance Tuning, Query Optimization, SQL Stored Procedures, SQL Databases, Speech Recognition, Scripting, Fast Healthcare Interoperability Resources, Large Language Models, Database Optimization, Agentic-AI, Information Technology, Health Level Seven International, Enterprise Integration, Machine Learning Operations, Virtual Agents, Model Context Protocol, Data Pipelines - **Published:** October 9, 2026 - **Apply:** https://www.disabledperson.com/jobs/75857151-ai-engineer ## About the Role * Bachelor's degree in Computer Science, Data Engineering, Data Science, or a related field, or equivalent practical experience. * 3+ years experience in Python and SQL for data engineering, AI development, and scripting. * Strong proficiency with MS SQL, including experience creating stored procedures, complex queries, and database optimization. * Demonstrated experience designing and implementing ETL pipelines and data transformation workflows. * Experience or coursework in AI, NLP, voice technologies, or image processing. * Understanding of building, configuring, or deploying AI agent frameworks (e.g., using APIs, tool integrations, or MCP). * Ability to work with multimodal data (voice, images, and text) and structure it for AI consumption. * Strong analytical, problem-solving, and communication skills. * Detail-oriented and able to document and communicate technical processes clearly. Preferred Qualifications * Advanced MS SQL skills, including performance tuning, indexing strategies, and query optimization. * Experience with data warehousing concepts and dimensional modeling. * Experience working with voice APIs (e.g., speech recognition/generation), image processing libraries, or ML Ops tools. * Exposure to healthcare IT systems, HL7/FHIR standards, or regulatory compliance (HIPAA). * Familiarity with data integration tools and techniques for healthcare data sources. * Awareness of AI ethics, bias, and responsible AI development * . ## Description * Design and implement robust data pipelines and ETL processes to ingest, cleanse, and transform large healthcare datasets that provide essential context for AI agents. * Develop and optimize stored procedures, complex queries, and database architecture in MS SQL to support AI agent functionality and analytics. * Build, iterate, and maintain AI agents capable of understanding and generating voice, text, and image data to automate critical workflows. * Create and maintain data infrastructure that enables AI agents to access structured and unstructured information from diverse healthcare systems. * Collaborate with cross-functional teams to define user needs and business goals for AI agents in healthcare/radiology environments. * Develop, test, and optimize prompts for LLMs integrated into AI agents, with a focus on multimodal (voice and image) capabilities. * Work with APIs, tools, and Model Context Protocol (MCP) to integrate third-party services and expand agent functionality. * Use Python and SQL extensively to support agent automation, data transformation, analytics, and backend integration. * Evaluate agent performance; analyze multimodal outputs (transcriptions, image analysis, etc.) and refine as needed. * Document workflows, data architectures, prompt strategies, and agent systems for internal teams. * Support efforts to improve data security, compliance, and responsible AI use.