Ai Engineer Jobs

About The Position

Requirements

• At least 3 years of professional software or data engineering experience, with strong Python and SQL skills.
• Experience building and shipping at least one LLM-powered application or agent that real users depend on, using tool calling, retrieval, structured outputs, and evaluation.
• Hands-on Databricks experience (Spark, Delta Lake, Unity Catalog, and Workflows) or experience with a comparable lakehouse, or sufficiently deep data engineering experience to ramp up quickly.
• Experience integrating SaaS and internal systems through REST APIs, webhooks, and OAuth.
• Ability to test and instrument work, consider costs, and determine when a workflow is ready to be handed off.
• Clear communication with nontechnical stakeholders and comfort leading working sessions with business teams.
• Experience using AI coding assistants such as Claude Code or GitHub Copilot in a modern engineering workflow.
• Bachelor’s degree in computer science or a related field, or equivalent practical experience.

Nice To Haves

• Experience with Databricks Mosaic AI (Agent Framework, Model Serving, or Vector Search), Genie, Lakeflow Declarative Pipelines, Lakebase, or Databricks Apps.
• Experience building MCP servers or working with the Claude Developer Platform or Agent SDK.
• Experience with workflow orchestration tools such as n8n.
• Experience integrating HubSpot, Zendesk, NetSuite, or Jira.
• Experience in ad tech, performance marketing, or another environment handling regulated consumer data.

Responsibilities

• Ship production agents and automated workflows from a prioritized, business-validated backlog.
• Own workflows from scoping with business owners through building, deployment, monitoring, documentation, and handoff.
• Build the Databricks data foundation for workflows, including Unity Catalog tables and views, Lakeflow pipelines, Lakeflow Connect ingestion, and Genie spaces.
• Bring data from ad-serving and partner platforms, CRM, support, and finance systems into a trusted, accessible place.
• Work with Data Science to measure agent quality through evaluation sets, accuracy and drift tracking, cost and latency instrumentation, audit fields, and failure alerts.
• Integrate systems through APIs, webhooks, MCP servers, and orchestration tools such as Databricks Workflows, n8n, and GitHub Actions; replace brittle automations with maintained, observable workflows.
• Partner with Core Engineering to expose platform data and actions as APIs for agents and business teams.
• Build reusable components such as Claude skills, MCP connectors, prompt and evaluation libraries, and playbooks.
• Handle consumer data according to Fluent’s privacy and compliance standards, use approved AI tools, and coordinate with IT and Security on credentials and access.
• Demo work weekly, document it in Confluence, and share learning in brown bags and tech talks.
• Use AI-assisted development tools, including Claude Code and GitHub Copilot review, as part of the regular workflow.

Benefits

• Competitive compensation and bonus.
• Career and professional growth opportunities.
• Health, dental, and vision insurance.
• Pre-tax savings plans and transit/parking programs.
• 401(k) with competitive employer match.
• Volunteer and philanthropic activities throughout the year.
• Educational and social events.
• Fully stocked kitchen and catered breakfast and lunch.
• Recreational sports leagues, networking opportunities, and quarterly team outings.