Agentic AI Engineer

Franklin Fitch; Atlanta (GA); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Equity

Competitive base salary

Performance upside

Job summary

Franklin Fitch is seeking an AI engineer to ship production-grade agent systems for enterprise clients. You will own end-to-end technical delivery across multiple engagements from day one, building custom agents in Python and deploying no-code workflows where appropriate.

The role is onsite in Atlanta with 3 days in office and involves presenting to executives, integrating agents with CRMs and APIs, and creating reusable templates to shorten future deliveries.

Qualifications

• Client-facing from day one, presenting to executives
• Experience with agent orchestration frameworks
• Ability to build and deploy no-code automations (Make, n8n, Zapier)
• Experience connecting agents to real systems via APIs
• Knowledge of RAG, vector databases and prompt engineering
• Familiarity with at least one cloud AI platform (Azure AI Foundry, AWS Bedrock or GCP Vertex)
• Ability to discuss AI solutions with non-technical executives

Responsibilities

• Own the full technical delivery of 2 client engagements within your first 90 days, scaling to 3–5 concurrent by month 12
• Build custom production agents using Python and Azure AI Foundry
• Deploy workflow automation via no-code/low-code tools where appropriate
• Integrate agents into real business systems: CRMs, APIs, internal tools
• Package reusable templates, blueprints, and integration patterns to compress delivery time

Skills

Client-facing

Executive communication

Hands-on with AI agents

Tools

Python

Azure AI Foundry

Make

n8n

Zapier

APIs

Job description

Most AI engineers build agents. Few ever see them run in the real world.

This role is different.

You'll be shipping AI agents into production at real organizations - construction companies, manufacturers, real estate firms - and measuring success by the business outcomes those agents generate, not by the demo. You'll be doing it across 3-5 client engagements simultaneously by the end of your first year.

What you're joining

A fast-growing AI consultancy that deploys agentic solutions for enterprise clients across industries. Small team. High standards. Founders still in the work. The kind of shop where your instincts shape delivery approach, your reusable components become the firm's IP, and your track record is real and attributable.

This is not an internal tooling role, a research position, or a "prompt engineer" job with a new title.

What makes this role unusual

You won't be locked into one delivery approach. You'll build custom agents in Python when the problem demands it, and reach for Make, n8n, or equivalent platforms when speed and pragmatism are the right call. The judgment of when to use each is considered as important as the technical ability to execute both.

You'll also be client-facing from day one -- presenting to executives, running discovery on messy workflows, and translating ambiguous business problems into working AI solutions.

What you'll actually be doing

• Owning the full technical delivery of 2 client engagements within your first 90 days, scaling to 3--5 concurrent by month 12
• Building custom production agents using Python and Azure AI Foundry - not prototypes
• Deploying workflow automation via no-code/low-code tools where appropriate
• Integrating agents into real business systems: CRMs, APIs, internal tools
• Packaging reusable templates, blueprints, and integration patterns that compress delivery time on future engagements

What the role requires

• 3 days a week onsite in Atlanta
• Hands-on experience with at least one agent orchestration framework
• Comfort building and deploying no-code automations (Make, n8n, Zapier)
• Experience connecting agents to real systems via APIs and function calling
• Working knowledge of RAG, vector databases, and prompt engineering
• Familiarity with at least one cloud AI platform ideally Azure AI Foundry, but AWS Bedrock or GCP Vertex acceptable also.
• The ability to talk to a non-technical executive about how an agent works and keep them engaged

Bonus: TypeScript/Node.js, MCP/A2A protocol knowledge, public GitHub presence or published writing on agent development.

What's on offer

Competitive base + performance upside and equity.