Type: Full-timeCompany: Friday Media Group (FMG)About the Role:
We are building a next-generation
AI Agent Platform
across our group, alongside deploying specialised AI agents within our products and business wide operations. We are looking for a
hands-on AI Engineer
with strong experience in:
-
building and deploying AI agents
-
designing
production-grade RAG (Retrieval-Augmented Generation) systems
-
working with frameworks such as
LangChain and CrewAI
This is not a research role.
We are looking for someone who has
built and shipped real AI systems into production environments
.
What You Will Be Working On:
-
Designing and building
multi-agent systems
for real-world business workflows
-
Developing agents across:
-
Finance
-
Customer support automation
-
Marketing workflows
-
Sales and CRM automation
-
Building
RAG-powered systems
to enable agents to retrieve and reason over internal data
-
Integrating AI agents with real systems:
-
NetSuite
-
N8N
-
CRMs
-
Email systems
-
Internal APIs and databases
-
Creating
hybrid systems combining rules, workflows, and LLM reasoning
-
Implementing structured outputs (JSON, workflows, automation triggers)
Key Responsibilities:
-
Build, test, and deploy
AI agents end-to-end
-
Design
agent architectures
(single-agent, multi-agent, tool-using agents)
-
Develop and optimise
RAG pipelines
, including:
-
document ingestion and chunking strategies
-
embedding pipelines
-
vector search and retrieval optimisation
-
grounding LLM outputs with internal data
-
Implement
context management, memory, and tool usage
within agents
-
Hands on experience with N8N or similar workflow automation tools
-
Integrate agents with external APIs, databases, and SaaS platforms
-
Build evaluation, monitoring, and logging systems for agent performance
-
Optimise for
accuracy, latency, and cost efficiency
-
Work closely with product teams to translate workflows into AI-driven systems
Required Skills & Experience:
-
Strong experience in
Python
-
Hands-on experience with:
-
LangChain
-
CrewAI
(or similar multi-agent frameworks)
-
Proven experience building
production-grade AI agents
-
Strong experience with
RAG systems
, including:
-
embeddings and vector search
-
retrieval optimisation (filters, hybrid search, ranking)
-
grounding outputs with structured and unstructured data
-
Experience working with
vector databases
such as:
-
Pinecone
-
or alternatives (Weaviate, FAISS, etc.)
-
Experience with LLM APIs (OpenAI, Gemini, etc.)
-
Strong understanding of:
-
prompt design
-
tool/function calling
-
memory and context handling
Preferred (Nice to Have):
-
Experience building AI agents in:
-
Finance (AP, AR, reporting, forecasting)
-
Marketing automation
-
Sales / CRM workflows
-
Customer support systems
-
Experience with
fine-tuning or adapting models
, including:
-
instruction tuning
-
domain adaptation
-
evaluation of fine-tuned vs prompt-based approaches
-
Experience with advanced RAG patterns:
-
hybrid search (vector + keyword)
-
re-ranking models
-
agent-driven retrieval strategies
-
Experience with:
-
Supabase / PostgreSQL
-
FastAPI or similar backend frameworks
-
event-driven or workflow-based systems
-
Exposure to NetSuite or financial systems is a strong plus
What We Are Looking For:
-
Someone who has
actually built and deployed AI agents
, not just experimented
-
Strong problem solver who can translate business workflows into AI systems
-
Comfortable working in a
fast-moving, product-driven environment
-
Ability to balance:
-
LLM reasoning
-
deterministic rules
-
system design
Important Note
We are not looking for basic “chat with documents” implementations.
We are building
production-grade AI systems integrated with real business workflows and decision engines
.
Why Join Us:
-
Work on
real-world AI deployment
, not just prototypes
-
Build systems that directly impact business operations
-
Opportunity to shape a
group-wide AI platform (FridayOS vision)
-
Exposure to multiple domains: finance, marketplaces, SaaS, recruitment