Bachelor's degree in computer science, engineering, or related field, or equivalent experience.
5+ years of software, data, or AI engineering experience, including production AI delivery.
Strong skills in Python, SQL, API development, and software engineering.
Hands-on experience with LLM applications, including tool calling and multi-step workflows.
Experience integrating AI applications with enterprise databases and services.
Proficient in Tableau and Power BI, including dashboard development and data modeling.
Familiarity with Databricks, including notebooks and SQL.
Responsibilities
Develop IRIS's agent architecture and conversational capabilities.
Translate business requirements into AI capabilities and measurable criteria.
Connect IRIS to approved warehouse views, APIs, and reference data.
Implement natural language querying and source-grounded responses.
Integrate product-name matching and entity resolution across domains.
Develop and maintain Tableau and Power BI dashboards for product analysis.
Deploy and monitor AI services for reliability and performance.
Benefits
Collaborative work environment with domain experts and BI developers.
Opportunities for mentorship and team development.
Access to cutting-edge AI technologies and tools.
Involvement in impactful projects related to data integration and analysis.
Full Job Description
Job Description
Position Overview
We are 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 ideal candidate combines AI agent development expertise with strong data engineering skills, hands-on Tableau and Power BI experience, and working knowledge of Databricks.
Key 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.
Qualifications
Required qualifications:
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.
Some 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 the ability to collaborate with technical teams and business stakeholders.
Preferred qualifications:
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.
Preferred: Databricks and AWS certification
About SAIC
Science Applications International Corporation (SAIC) is a technology integrator in the technical, engineering, intelligence, and enterprise information technology markets. SAIC has approximately 26,000 employees and operates in more than 70 countries. The company was founded in 1969 and is headquartered in Reston, Virginia. SAIC provides services to the U.S. government, including the Department of Defense, the intelligence community, and civilian agencies. The company also serves commercial customers in the healthcare, energy, and financial services sectors.
