AI Engineer

SAIC•College Park, MD

10d

About The Position

SAIC is seeking a Senior AI Engineer to design, develop, and deploy IRIS, an AI agent supporting the HFDP Data Integration project. IRIS will help users discover, connect, and understand product information across investigations, inspections, and recalls using enterprise data warehouse resources. The role combines AI agent development with data engineering and hands-on Tableau, Power BI, and Databricks work.

Requirements

Bachelor’s degree in computer science, engineering, or a related field, or equivalent practical experience.
5+ years of relevant software, data, or AI engineering experience, including production AI delivery.
Strong Python, SQL, API development, and software engineering skills.
Hands-on experience developing LLM applications with tool calling, structured outputs, retrieval-augmented generation, and multi-step agent workflows.
Experience integrating AI applications with enterprise databases and services.
Hands-on experience with both Tableau and Power BI, including dashboard development, data modeling, calculations, and report validation.
Familiarity with Tableau calculated fields and Power BI DAX and Power Query.
Practical Databricks experience, including notebooks, SQL, and working with existing data workflows.
Experience with AI evaluation, automated testing, Git, CI/CD, and cloud deployment.
Strong communication skills and ability to collaborate with technical teams and business stakeholders.

Nice To Haves

Experience with product entity resolution, semantic search, embeddings, and vector retrieval.
Familiarity with Databricks Delta tables, PySpark, MLflow, or Unity Catalog.
Experience with BI access controls, refresh processes, and performance optimization.
Experience developing AI agents in enterprise or regulated environments.
Familiarity with investigations, inspections, recalls, or regulatory data.
Experience implementing source citations, human review workflows, and audit logging.
Databricks and AWS certification.

Responsibilities

Develop IRIS’s agent architecture, conversational capabilities, workflows, and tool integrations.
Translate business requirements into AI capabilities and measurable acceptance criteria.
Connect IRIS to approved warehouse views, APIs, reference data, and documentation.
Implement natural language querying, retrieval, and source-grounded responses.
Integrate product-name matching and entity resolution to connect records across domains.
Develop and maintain Tableau and Power BI dashboards and reports supporting product analysis and validation of IRIS results.
Work with Tableau data sources and Power BI semantic models to maintain consistent business definitions and metrics.
Use Databricks notebooks, SQL, and existing workflows to support data preparation, experimentation, and AI integration.
Implement access controls, human review, error handling, and traceability.
Build evaluations for response accuracy, retrieval relevance, tool execution, and task completion.
Deploy and monitor AI services for reliability, performance, usage, and cost.
Collaborate with domain experts, BI developers, data engineers, and architects; document solutions and mentor team members.