Agentic AI Engineer

Franklin Fitch; Atlanta (GA); Hybrid; USD 120,000 - 190,000; Full time

Job summary

Franklin Fitch is a fast-growing AI consultancy that deploys agentic solutions for enterprise clients. You will ship AI agents into production at hospitals, manufacturers, fintechs, and real estate firms, measuring success by business outcomes rather than demos.

You’ll be client-facing from day one, presenting to executives, and translating complex problems into working AI solutions. You’ll own 2 engagements in 90 days, scale to 3–5 concurrently by year one, and build reusable templates to speed

Qualifications

• Hands-on experience delivering AI agents
• Ability to translate business problems into AI solutions
• Comfort presenting to executives and running discovery on workflows
• Experience connecting agents to real systems via APIs and function calls
• Familiarity with RAG, vector databases, and prompt engineering
• Knowledge of at least one cloud AI platform (AWS Bedrock, Azure AI Foundry, or GCP Vertex)
• Ability to work in a fast-paced client-facing consultancy environment

Responsibilities

• Own delivery of 2 client engagements in 90 days, scaling to 3–5 concurrent by year 1
• Build production agents in Python and LangChain/LangGraph when appropriate
• Deploy workflow automation via no-code/low-code tools where suitable
• Integrate agents into CRM systems, APIs, and internal tools
• Create reusable templates, blueprints, and integration patterns to shorten future engagements

Skills

Agent delivery

Python

LangChain

LangGraph

No-code automation

APIs & function calling

Executive communication

Client-facing delivery

Onsite collaboration

Tools

Make

n8n

Zapier

LangChain

LangGraph

Python

AWS Bedrock

Azure AI Foundry

GCP Vertex

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 - hospitals, manufacturers, fintechs, 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 production agents using Python and LangChain/LangGraph (or equivalent) -- 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 (AWS Bedrock, Azure AI Foundry, or GCP Vertex)
• 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.