AI Engineer

PowerPlan•Atlanta, GA

17d•Hybrid

About The Position

PowerPlan is hiring an AI Engineer as one of the first members of its Applied AI team. The role is an in-house, forward-deployed engineering position that works like a product owner, owning AI solutions end to end—from understanding a department’s needs through delivering tools people use regularly. The engineer will embed with teams across the company, including customer support, professional services, finance, and sales, and build solutions with substantial autonomy. The position reports to the VP of Strategic Initiatives, whose group works closely with PowerPlan’s executive leadership on the company’s top priorities. The engineer will also help establish how the new team operates. Success is measured by the number of solutions brought into weekly use, the measurable improvement each delivers, and whether departments can operate and update their tools independently. The role includes learning work directly from department staff, establishing problem statements and baselines before building, piloting and scaling solutions, developing reusable agent skills and workflow patterns, and setting standards for AI quality and appropriate human review. The engineer will leave departments with runbooks, training, and staff able to maintain and change the solutions.

Requirements

Two to four years of professional experience building or shipping software products as an engineer, product manager, or in a similar role; alternatively, a related master’s degree and at least one year of that experience.
Experience shipping software or a product that other people rely on, and ability to explain what was built, why, and what changed after people used it.
Systems thinking and first-principles reasoning, including the ability to demonstrate a process changed rather than merely sped up.
Ability to turn conversations with subject-matter experts into clear problem statements and measurable definitions of success.
Agentic coding tools such as Claude Code, Codex, Cursor, or OpenCode are the default working approach; ability to plan work, direct the tool, and check its output.
Ability to write working Python or JavaScript, or build working software with agentic coding tools, and use SQL and APIs.
Ability to explain tradeoffs plainly and teach others to change a tool themselves.
Bachelor’s degree in computer science, computer engineering, information systems, industrial or systems engineering, or a closely related field.
Based in Atlanta and able to work in the office at least three days per week.
Authorized to work in the United States; the role is not eligible for visa sponsorship now or in the future.

Nice To Haves

A minor or coursework in business, economics, or finance, or work experience in or alongside finance, accounting, professional services, or customer support.
Experience with continuous improvement methods such as Lean, Six Sigma, or value stream mapping.
Experience automating workflows inside business systems or building agent skills, MCP connections, or other reusable components for AI tools.
A related master’s degree, such as in computer science, information systems, data science, or business analytics.

Responsibilities

Embed with departments and learn how work is performed directly from the people who do it.
Before building, agree on a one-page problem statement, a measured baseline, and real examples.
Help create the new team’s playbook, including standards for building with AI tools, keeping shared work current, and testing quality and robustness.
Get the first solution into weekly pilot use by the end of the first quarter and measure time saved against the baseline.
Grow to one or two solutions in weekly use by month six and three solutions across at least two departments by year end.
Build two larger cross-department solutions with the team’s AI data engineer.
Redesign clumsy workflows in collaboration with the people who run them, rather than merely speeding them up.
Use agentic coding tools as the default way of building.
Provide runbooks and training so departments can operate and change delivered tools independently.
Publish reusable agent skills and workflow patterns by month six, grow them into a company library, and help define standards for when AI output can be trusted and when human review is needed.