Senior Software Engineer, AI

Backstage•Burbank, CA

73d•$130,000 - $165,000

About The Position

We are looking for a highly skilled Senior AI Software Engineer to design and build smart, user-facing AI features that make complex business workflows simple, intuitive, and insightful. In this hands-on role, you'll work across the full AI/ML stack to bring intelligent experiences-such as context-aware chatbots, AI-driven data explanations, automated task guidance, and interactive forecasting dashboards-to life. This is a unique opportunity to shape how users interact with data, make decisions, and complete critical tasks across payroll, compliance, and labor management systems-using cutting-edge AI tools like LLMs, embeddings, and Model Context Protocol (MCP).

Requirements

5-8 years of professional software engineering experience, with significant hands-on AI/ML application development.
Strong programming skills in Python, TypeScript, and Node.js, including experience building and integrating backend APIs.
Experience building with LLMs, embeddings, and prompt engineering, especially for chat, recommendations, or summarization tasks.
Familiarity with Model Context Protocol (MCP) or similar frameworks for managing long-lived AI context.
Proficiency in cloud platforms (preferably AWS) and data technologies (e.g., PostgreSQL, Redis, DynamoDB).
Passion for delivering intuitive, AI-enhanced user experiences through strong cross-functional collaboration.

Nice To Haves

Experience building AI features in productized environments-such as guided workflows, task automation, or user-facing insights.
Familiarity with LangChain, Semantic Kernel, or similar orchestration frameworks.
Knowledge of forecasting models, causal inference, or time-series prediction in business/product contexts.
Experience building natural language interfaces over structured business data.
Background in payroll, HR tech, fintech, or operational compliance is a plus.

Responsibilities

Design and develop context-aware AI assistants and chatbots that help users navigate complex workflows and answer domain-specific questions.
Build AI-guided task assistants that proactively surface recommendations, fill in missing data, or automate next steps in real-time.
Implement explainable AI (XAI) features that help users understand insights, predictions, or system decisions transparently.
Develop AI-driven dashboards and prediction engines that provide instant insights into user actions, financial trends, labor forecasts, and potential compliance risks.
Build self-service AI tools that allow users to ask natural language questions of their data and receive visual, interpretable responses.
Collaborate with UX and product teams to embed these insights directly into the application experience.
Build scalable backend services in Python, TypeScript, and Node.js, integrating with LLMs, vector stores, and analytics engines.
Use Model Context Protocol (MCP) to manage and preserve context across chat, prediction, and recommendation workflows.
Leverage cloud-native tools (AWS Lambda, SageMaker, Bedrock, DynamoDB) to deploy and scale AI features.
Write clean, production-quality code and participate in architectural reviews, technical design, and agile ceremonies.
Work closely with data scientists, designers, and other engineers to prototype and ship AI-powered product experiences.
Continuously evaluate emerging AI tools, LLM frameworks, and APIs to push the product's intelligence capabilities forward.