AI Engineer at Fluent - Build LLM Agents in Ad Tech

Fluent, LLC; New York (NY); Remote; USD 130,000 - 155,000; Full time

Benefits offered by this job

Health, dental, and vision insurance

401(k) with employer match

Pre-tax savings plans and transit/park

Job summary

Fluent, LLC is hiring its first AI Engineer to build production-grade LLM-powered agents and automated workflows in a fully remote, US-wide role. You will own data pipelines in a Databricks lakehouse, integrate with ad-tech systems, and collaborate with Data Science and Solution Architecture to deliver measurable impact.

The role emphasizes ownership, strong Python/SQL skills, and experience with Claude/GitHub Copilot.

Qualifications

• 3+ years of professional software or data engineering experience.
• Built and shipped at least one LLM-powered application or agent used by real users.
• Hands-on Databricks or equivalent lakehouse experience.
• Experience integrating SaaS and internal systems via REST APIs, webhooks, OAuth.
• Tests, instrumentation, and cost-awareness in workflows.
• Able to communicate with non-developers and run sessions with a business team.
• Experience using AI coding assistants (Claude Code, GitHub Copilot).
• Bachelor's degree in computer science or related field, or equivalent experience.

Responsibilities

• Ship production agents and automated workflows from backlog through handoff.
• Build data foundation in Databricks (Unity Catalog, Lakeflow) and integrate sources.
• Collaborate with Data Science to measure quality and add evaluation metrics.
• Integrate Fluent systems via APIs, webhooks, MCP servers, and orchestrations.
• Expose platform data and actions as APIs for business users.
• Create reusable components and playbooks for Fluent’s teams.
• Ensure consumer data handling aligns with privacy and security standards.
• Document learnings in Confluence and share in sessions.

Skills

Python

SQL

LLM-powered app

Databricks

REST APIs

Testing & instrumentation

Communication

AI coding assistants

Bachelor's degree

Education

Bachelor's degree in computer science or related field

Tools

Databricks

GitHub Actions

Claude Code

Job description

AI Engineer at Fluent - Build LLM Agents in Ad Tech — Remote

Pioneering Role with High Visibility: Being Fluent's first dedicated AI Engineer is a double-edged sword — you have enormous impact and ownership, but you are also defining the function from scratch with limited institutional support. This is ideal for someone who thrives with autonomy, but potentially risky for someone who needs established mentors in the AI space.

Compensation vs. Market: The $130k–$155k base (plus bonus) is competitive for a mid-level AI/ML engineer nationally, but sits below the top-of-market for senior AI engineers in major tech hubs ($170k–$220k+). The "first AI hire" positioning and bonus could compensate, and there is implicit upside if the function grows and you move into a lead role.

• Production LLM agents and agentic workflows (top-10 most sought-after skills in 2024–2025)
• Databricks ecosystem depth (Unity Catalog, Lakeflow, Mosaic AI)
• MCP server architecture and Claude/Anthropic tooling
• End-to-end ownership of data pipelines in a regulated (ad tech/consumer data) context

Green Flags: Clear 90-day and 6-month success metrics signal an organized hiring process. Cross-functional exposure (Data Science, Engineering, Business) builds well-rounded product instincts. Reusable component mandate prevents technical debt accumulation.

Red Flags to Watch: "Alongside day jobs" AI history means you may inherit undocumented, ad-hoc systems. Clarify in interviews how much time will be spent fixing legacy automations vs. building new ones.

Fluent is building the next generation advertising network: Partner Monetize and Advertiser Acquisition. Our vision is to build an ML/AI first network of advertisers and publishers working toward a common objective, elevating relevancy in e-commerce for everyday shoppers.

Fluent is hiring its first dedicated AI Engineer. Over the past year, AI at Fluent has moved from pilots to production: a service desk agent that closes tickets without a human touch, a pipeline that cut modeled audience delivery from days to hours, and an agent that audits cross-system attribution and identifies revenue reconciliation opportunities. All of it was built by people doing it alongside their day jobs. Your job is to make it your day job.

You will sit in Core Engineering and work every day with Data Engineering, Data Science, and Solution Architecture. You will build the agents and automated workflows our business teams have asked for, and you will build them on the Databricks lakehouse that is Fluent's data hub, because the hard part of most of these workflows is not the model — it is getting trusted data and reliable actions in front of it.

You are a builder who ships. 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. You are comfortable sitting with a support lead or an account manager, understanding how they actually work, and turning that into something that runs every day.

This role is fully remote in the United States, with occasional travel to our New York headquarters.

What You'll Do

• 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.

What Success Looks Like

In your first 90 days you will have shipped one workflow end to end, with a named business owner and numbers Finance can validate. By six months you will have several in production, at least one reusable component another builder has picked up, and a clear view of what next quarter's backlog should be.

Requirements

• 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.

Nice to Have

• 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.

At Fluent, we like what we do, and we like who we do it with. Our team is a tight-knit crew of go-getters; we love to celebrate our successes! In addition, we offer a fully stocked kitchen, catered breakfast and lunch, and our office manager keeps the calendar stocked with activity-filled events. When we are not eating, working out, or planning parties, Fluent folks can be found participating in recreational sports leagues, networking with She Runs It, and bonding across teams during quarterly outings to baseball games, fancy dinners, and pizza-making classes. And we have all the practical benefits, too:

• Competitive compensation
• Ample 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
• The amazing opportunity to work for a high-flying performance marketing company!

Salary Range: $130,000 to $155,000 plus competitive bonus. The base salary range represents the low and high end of the Fluent salary range for this position. Actual salaries will vary depending on factors including but not limited to location, experience, and performance.

Anti-Fraud Notice: Candidates may be at risk of targeting by malicious actors seeking personal information. Fluent recruiters will only reach out via LinkedIn or email with an @fluentco.com domain. Any outreach by Fluent via other sources (e.g. text, other domains, etc.) should be ignored.

Fluent participates in the E-Verify Program. As a participating employer, Fluent, LLC will provide the Social Security Administration (SSA) and, if necessary, the Department of Homeland Security (DHS), with information from each new employee's Form I-9 to confirm work authorization. Fluent, LLC follows all federal regulations including those set forth by The Office of Special Counsel for Immigration-Related Unfair Employment Practices (OSC). The OSC enforces the anti-discrimination provision (274B) of the Immigration and Nationality Act (INA), 8 U.S.C. 1324b.

Is this AI Engineer role truly fully remote? Yes, the role is fully remote within the United States. However, occasional travel to Fluent's New York City headquarters is expected. What is the salary range for this position? The base salary range is $130,000 to $155,000 annually, plus a competitive bonus. Actual pay depends on location, experience, and performance. Do I need prior Databricks experience to apply? Hands-on Databricks experience is preferred, but candidates with deep data engineering experience in a comparable lakehouse platform are encouraged to apply, as the expectation is you can ramp quickly. Is this a senior or mid-level role? The role requires 3+ years of software or data engineering experience and at least one shipped LLM-powered application, placing it at a mid-to-senior level. It is Fluent's first dedicated AI Engineer hire, so it carries significant ownership and autonomy. What LLM frameworks and tools does this role use? The role centers on the Claude/Anthropic ecosystem (Claude Code, Claude skills, MCP servers), Databricks Mosaic AI, and orchestration tools like n8n and GitHub Actions, alongside standard Python and SQL development.

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