Forward Deployed AI Engineer

JumpOff • Sandy Springs, GA

5h • Onsite

About The Position

Build AI systems for clients by working within their systems and data alongside their teams, taking solutions from prototype through production and into daily use. The role reports to the AI Engineering Lead and collaborates with people responsible for the business side of each engagement.

The work focuses on building data pipelines, integrations, LLM-based workflows, and the testing and monitoring needed to support them. It also includes working with clients to understand their data and systems, creating shared reusable tools across engagements, and documenting solutions so client teams can operate them. The position is based in Atlanta, working from the Sandy Springs office, and includes travel to client sites up to about 30% of the time.

The role offers exposure to production AI deployments across industries and technology stacks, business-outcome scoping, frontier AI tools and supported certifications, and production AI engineering standards. It is intended to develop engineers who can deliver reliable production AI and explain technical work to business stakeholders. The role can grow as the engineer demonstrates increased ownership.

Requirements

• At least 3 years of experience building and shipping software relied on in production.
• Strong Python and SQL skills.
• Experience building APIs and integrations to move data between systems and keep systems synchronized.
• Hands-on deployment experience on AWS, Azure, or GCP.
• Experience with LLMs in production or close to production, including evaluating output before it reaches users.
• Daily use of coding agents and the discipline to check their output.
• Ability to explain technical choices clearly to nontechnical stakeholders.
• Discretion when handling client data and firm-level information.
• Based in Atlanta and able to work from the Sandy Springs office, travel to clients, and eligible to work in the US.

Nice To Haves

• Experience in a customer-facing technical role such as solutions, implementation, or forward-deployed engineering.
• Startup experience or experience building something from zero.
• Experience with Microsoft or AWS data and AI services.
• Experience working with sensitive or regulated data, such as HIPAA, SOC 2, or financial data.

Responsibilities

• Build and deploy AI solutions in client environments, including data pipelines, client-system integrations, LLM-based workflows and agents, and user-facing applications.
• Work with client technical teams on access, environments, and security.
• Test model output before it reaches users and monitor it after deployment.
• Troubleshoot production issues and improve solutions based on how people use them.
• Turn one-off builds into reusable components for future engagements.
• Document solutions so client teams can run them.
• Travel to client sites, up to about 30% of the time.
• Perform other duties as assigned.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed