Forward Deployed AI Analyst

re-zoo-me; Raleigh, Northern (NC, KY); Hybrid; USD 100,000 - 110,000; Full time

Job summary

Makai Labs is seeking an Forward Deployed AI Analyst to train with engineering, product, and client teams, then embed in client engagements to automate workflows.

This is an early‑career role where you become a subject matter expert quickly and iterate on prototypes to improve client workflows.

Qualifications

• Seniors, recent graduates, and early-career candidates with ownership.
• Experience building or leading a project, tool, or startup is valued.
• Ability to map workflows and define automation opportunities.

Responsibilities

• Spend initial month in training and shadowing before leading end-to-end workflow work.
• Interview client SMEs, read documents, and map involved systems to identify automation targets.
• Write specifications with the client team and prototype on Makai's platform.
• Oversee rollout and measure productivity and ROI; adapt plans as needed.
• Some projects may stop at discovery or fail prototype testing.

Skills

Python

JavaScript

SQL

APIs

Workflow automation

LLMs

Data analysis

Dashboards

QA testing

Agile delivery

Team leadership

Tools

Jira

Azure DevOps

Job description

Makai Labs builds AI systems that automate real work inside companies. As a Forward Deployed AI Analyst, you will train with Makai’s engineering, product, and client teams, then embed in one of our client engagements to find the workflows worth automating and build AI agents that handle them. You will work directly with the people who run the business, and your work is done when their teams rely on what you built.

This is an early‑career role. You will see how a company actually runs from the inside, rapidly become a subject matter expert, and iterate on prototypes to improve their workflows.

Responsibilities

You will spend about your first month in training and shadowing, then take one workflow end to end alongside a Makai lead before working more independently.

Engagements vary, but most follow the same arc. You start by learning how the work is done today. Discovery tasks include interviewing client Subject Matter Experts (SMEs), reading the documents they work from, and mapping the systems involved. Based on this discovery, you propose what to automate, work with the client team to write the spec, and build a prototype on Makai's platform. Makai engineers support the technical work throughout. If the prototype holds up with client practitioners, you run the rollout and measure productivity and ROI.

Not every project reaches every stage. Some end at discovery, and some prototypes don't survive user testing. Part of the job is figuring out what won’t work, so that we can focus our effort optimally.

Over time, Analysts will get put onto career development tracks toward AI engineering, product and implementation, or engagement leadership, depending on performance and interest.

Example Problems

• A finance team spends days manually reading data from PDFs, entering them into giant spreadsheets, running internal formulae and drafting reports based on these results.
• A field operations team spends hours manually scheduling and resolving conflicts for employees using multiple disconnected platforms.
• A spreadsheet process has become a business‑critical system without clear ownership or controls.

Qualifications

We are looking for seniors, recent graduates, and early‑career candidates who want a path toward company leadership. An ideal candidate has shown ownership both inside and outside the classroom. That could mean you:

• Built a product, tool, model, startup, research system, or internal process.
• Led a club, team, lab effort, athletic group, event, or high‑pressure project.
• Took a messy internship project and turned it into something people used.

Technical Profile

• Python, JavaScript, SQL, or another programming/data‑analysis language.
• APIs, workflow automation, backend services, internal tools, or scripting.
• LLMs, retrieval, agents, structured outputs, prompt design, or AI evaluation.
• Data analysis, spreadsheets, dashboards, process mining, or financial/operating models.
• Product specs, user stories, QA testing, Jira, Azure DevOps, or agile delivery.
• Research, internships, startups, team leadership, athletics, or other high‑accountability work.

Very technical candidates may be considered for AI engineering or solutions engineering paths. Product- and operator‑oriented candidates may be considered for implementation, product, or business analysis paths.

Position Details

• Location: Remote‑friendly, with Eastern Time overlap preferred.
• Travel: Occasional travel may be required for training, client work, or company visits.
• Start timing: Paid IAP micro‑cohort (January 2027) and summer 2027 full‑time starts.
• Exceptional recent alumni may be considered for an earlier full‑time start.
• Sponsorship: No VISA sponsorship available at this time.

Compensation Range: $100K - $110K