Full Stack Software Engineer (AI)

• Burbank
• Hybrid
• Hourly salary: $88

Job Description add details here

We are building an agentic natural-language query layer for enterprise portfolio management reporting. This platform will deliver standardized data analytics and visualizations for enterprise portfolio management reporting. It will enable business users to ask plain-English questions about technology projects resources timelines budgets and milestones and receive accurate answers charts and dashboards.
This role will design build and maintain reporting solutions that integrate data from our portfolio management system and multiple upstream systems define key metrics and provide trusted actionable insights that enable leadership to make strategic data-driven decisions.
This is a greenfield build focused on architecture the semantic layer and the AI pipeline. The role will also support an existing Power BI environment as a separate workstream. Clear technical and functional documentation will be critical to maintainability adoption and stakeholder confidence.
ResponsibilitiesDesign and build a text-to-SQL pipeline that converts natural-language questions into safe permission-aware SQL a semantic layer that defines table relationships column meanings and business retrieval over schema documentation business logic and query examples to improve multi-step agent workflows that can clarify requests chain tool calls and recover from query LLM providers (OpenAI Anthropic etc.) for query generation orchestration and result guardrails for query validation cost limits row limits and permission-based evaluation processes to measure query accuracy and detect unsupported and build a clear analytical UI for results charts and AI-generated the existing Power BI environment including data models DAX measures and calculated and maintain API gateways for governed data access across the warehouse Power BI and AI portfolio reporting data project information and health metrics from tools such as Smartsheet Jira Clarity PPM ServiceNow and with data engineering to maintain clean well-documented warehouse technical and functional documentation including architecture APIs data dictionaries workflows and user with the Portfolio Management team and business stakeholders to define requirements and iterate on build and maintain automated dashboards that track performance metrics identify historical trends analyze forecast accuracy and visualize business value outcomes to drive data-backed prioritization planning prioritization stakeholder communication and delivery of high-quality code.
Basic Qualifications5 years of full-stack engineering experience with Python and/or TypeScript/JavaScript including strong server-side and API design SQL and data warehouse experience including schema design joins performance and platforms such as Snowflake BigQuery or -on experience with LLM APIs including prompt engineering tool calling structured outputs and experience with RAG architecture embeddings vector databases and common failure -end experience building analytical interfaces using React/ and charting or data-grid to work independently in ambiguous 0-to-1 environments and document key architecture technical and functional documentation designing governed API layers across multiple systems and UI/UX judgment with a focus on clear accessible data-driven engineering fundamentals including testing CI/CD version control code review and performance track record of developing comprehensive dashboards to monitor business performance focusing on financial health forecast-to-actual variance trend analysis pipeline prioritization and strategic outcome value communication skills with the ability to translate complex technical concepts for varied with LLM orchestration or agent frameworks such as LangGraph CrewAI AutoGen or custom state-machine evaluating LLM output accuracy and identifying unsupported or hallucinated QualificationsPower BI experience including data models DAX measures and calculated with portfolio tools such as Smartsheet or Clarity PPM and integrations with Jira SAP or with semantic layer tools such as dbt metrics Cube or and containerization experience using AWS GCP Azure or with caching layers such as Redis for latency-sensitive workloads.
Education
Bachelors degree in Computer Science Information Systems Software Electrical or Electronics Engineering or a comparable field of study and/or equivalent work