Software Engineer (AI Agents)

Fluent, Inc. is building production AI agents and automated workflows on its Databricks lakehouse. The Software Engineer (AI Agents) will partner with business teams and engineering functions to deliver, monitor, and maintain reliable workflows and the trusted data foundations they depend on.

Responsibilities:

• Ship production agents and automated workflows from a prioritized, business-validated backlog. Own each one from scoping with the business owner through build, deployment, monitoring, documentation, and handoff
• Build the data foundation those workflows depend on in Databricks: Unity Catalog tables and views, Lakeflow pipelines, Lakeflow Connect ingestion from systems like HubSpot, and Genie spaces that let business teams ask questions in plain language. Bring data from our ad-serving and partner platforms, CRM, support desk, and finance systems into one place people can trust
• Work with Data Science to make agent quality measurable: evaluation sets, accuracy and drift tracking, cost and latency instrumentation, and the audit fields and failure alerts every production workflow carries
• Integrate with Fluent's systems through APIs, webhooks, MCP servers, and orchestration (Databricks Workflows, n8n, GitHub Actions), and replace brittle point-to-point automations with maintained, observable ones
• Partner with Core Engineering to expose platform data and actions as APIs, so agents and business teams can use them directly instead of routing requests through engineers
• Build reusable pieces, not one-offs: Claude skills, MCP connectors, prompt and evaluation libraries, and playbooks that other builders across Fluent can pick up
• Handle consumer data in line with Fluent's privacy and compliance standards, use only approved AI tools, and work with IT & Security on credentials and access
• Demo weekly, write things down in Confluence, and share what you learn in brown bags and tech talks
• Use AI-assisted development (Claude Code, GitHub Copilot review) as a normal part of how you work

Requirements:

• You are strong in Python and SQL, you have put at least one LLM-powered application in front of real users, and you know the difference between a demo and a production system: evaluation, monitoring, cost, and a clear owner
• You have worked in Databricks or a comparable lakehouse, or you have the data engineering depth to get productive there quickly
• • 3+ years of professional software or data engineering experience, with strong Python and SQL
• • You have built and shipped at least one LLM-powered application or agent that real users depend on, using tool calling, retrieval, structured outputs, and evaluation
• • Hands-on experience with Databricks (Spark, Delta Lake, Unity Catalog, Workflows) or a comparable lakehouse, or deep enough data engineering experience to ramp quickly
• • Experience integrating SaaS and internal systems through REST APIs, webhooks, and OAuth
• • You test your work, instrument it, and care about cost. You know when a workflow is ready to be owned by someone else
• • You communicate clearly with people who do not write code, and you are comfortable running a working session with a business team
• • Experience using AI coding assistants (Claude Code, GitHub Copilot) as part of a modern engineering workflow
• • Bachelor's degree in computer science or a related field, or equivalent practical experience
• • Databricks Mosaic AI (Agent Framework, Model Serving, Vector Search), Genie, Lakeflow Declarative Pipelines, Lakebase, or Databricks Apps
• • Building MCP servers, or working with the Claude Developer Platform or Agent SDK
• • Workflow orchestration tools such as n8n
• • Integrations with HubSpot, Zendesk, NetSuite, or Jira
• • Experience in ad tech, performance marketing, or another environment that handles regulated consumer data