Sr. Software Engineer

Viant is looking for a Senior Software Engineer to join the Potens team and help evolve Magnus and Goliath, two internal platforms that power workflow orchestration and large-scale data exploration.

This is a hands-on, full-stack engineering role combining the modernization of mature production systems with the development of new AI-powered capabilities .

You’ll work across Java and Go backend services, browser-based JavaScript applications, data platforms, and emerging AI technologies.

A key part of the role will be expanding how users and authorized AI agents interact with our platforms from creating and managing workflows to exploring BigQuery data, generating and executing SQL, and securely accessing platform capabilities through AI tools.

We’re looking for an engineer who enjoys solving complex production problems, working across the stack, and owning software from design through deployment and ongoing support.

Magnus is a visual workflow orchestration platform supporting BigQuery, Cloud Storage, MySQL, REST APIs, email, FTP, conditional routing, parallel execution, Go and JavaScript scripting, YAML workflow definitions, debugging, audit history, and access controls.

Goliath is a lightweight, high-performance BigQuery development interface for writing and executing SQL, browsing datasets and tables, visualizing results, and managing cost and quota allocation without requiring direct access to the GCP Console.

As these platforms evolve, you’ll help expand their AI capabilities, including enabling users and authorized AI agents to:

• Create, understand, and modify Magnus workflows
• Discover, execute, and monitor workflows through MCP
• Explore BigQuery datasets and schemas through Goliath
• Generate, execute, and interpret SQL using AI
• Securely access platform capabilities through permission-aware AI tools

• Maintain and modernize Magnus Java applications, REST APIs, and Goliath’s JavaScript/jQuery frontend
• Develop and support backend capabilities using Java and Go
• Build production AI features and integrations using LLMs, tool calling, guardrails, evaluation, and MCP