Asks for

The ad says“Experience working in Agile, cross-functional engineering teams.”
The ad says“Expert-level Python development skills, including experience with FastAPI or Flask and asynchronous programming.”
The ad says“Experience deploying applications on Google Cloud Platform, including Cloud Run and Pub/Sub.”
The ad says“Strong understanding of embeddings, similarity search, and RAG design patterns.”
The ad says“Expert-level Python development skills, including experience with FastAPI or Flask and asynchronous programming.”
The ad says“Expert-level Python development skills, including experience with FastAPI or Flask and asynchronous programming.”
The ad says“Experience deploying applications on Google Cloud Platform, including Cloud Run and Pub/Sub.”
The ad says“Hands-on experience building GenAI applications using LangChain, LlamaIndex, LangGraph, or Google Vertex AI.”
The ad says“Hands-on experience building GenAI applications using LangChain, LlamaIndex, LangGraph, or Google Vertex AI.”
The ad says“Hands-on experience building GenAI applications using LangChain, LlamaIndex, LangGraph, or Google Vertex AI.”
The ad says“Hands-on experience building GenAI applications using LangChain, LlamaIndex, LangGraph, or Google Vertex AI.”
The ad says“Practical experience working with vector databases such as Pinecone, Milvus, Weaviate, or pgvector.”
The ad says“Practical experience working with vector databases such as Pinecone, Milvus, Weaviate, or pgvector.”
The ad says“Practical experience working with vector databases such as Pinecone, Milvus, Weaviate, or pgvector.”
The ad says“Experience deploying applications on Google Cloud Platform, including Cloud Run and Pub/Sub.”
The ad says“Expert-level Python development skills, including experience with FastAPI or Flask and asynchronous programming.”
The ad says“Strong understanding of embeddings, similarity search, and RAG design patterns.”
The ad says“Solid understanding of REST APIs, system integration, and secure service design.”
The ad says“Strong understanding of embeddings, similarity search, and RAG design patterns.”
The ad says“Practical experience working with vector databases such as Pinecone, Milvus, Weaviate, or pgvector.”

About Zinkworks

Zinkworks partners with leading Telecommunications and Financial Services organizations to modernize legacy systems, migrate mission-critical platforms to the cloud, and engineer AI-driven automation. From OSS transformation to rApp development and network intelligence, our teams simplify complexity and turn it into competitive advantage. Based in Ireland and operating across the EU, UK, and US, Zinkworks combines deep domain expertise with delivery excellence to help clients modernize faster and operate smarter.

The Opportunity

We are partnering with a major UK Telecommunications provider to deliver their flagship “Agentic AI” transformation programme. Operating from our Innovation Hub in Athlone, we are building a “CTO 2.0” ecosystem, moving our client from legacy, manual workflows to an intelligent, automated operating model powered by Autonomous AI Agents.

We are seeking a Senior Python / GenAI Developer who can take high-level architectural designs and turn them into production-ready software. You will build across the full application lifecycle, from a React-based “Agentic Canvas” frontend to Python services that orchestrate complex RAG pipelines and agentic workflows on Google Cloud Platform (GCP).

This is a hands-on engineering role at the cutting edge of applied GenAI, focused on building real systems that operate critical national infrastructure.

The Role

You will work closely with AI Architects, Solution Architects, DevOps Engineers, and Telecom SMEs to design and implement AI-powered applications that move beyond chatbots into tool-using, multi-step autonomous agents. You will be responsible for building robust, scalable, and secure systems that integrate AI models with real enterprise data and operational systems.

Key Responsibilities

Develop RAG Pipelines: Design and implement backend services in Python (FastAPI) to ingest, chunk, embed, and retrieve unstructured data such as PDFs, network schematics, and documentation.
Agent Orchestration: Implement agentic workflows using frameworks such as LangChain, LangGraph, or Vertex AI Agent Builder, enabling multi-step reasoning and tool execution.
Prompt Engineering & Optimisation: Design, test, and refine system prompts to ensure agents follow strict engineering rules while optimising for latency, reliability, and cost.
System Integration: Integrate AI agents with external APIs and enterprise systems such as Jira, ServiceNow, inventory systems, and internal platforms.
Cloud Deployment: Deploy and operate services on GCP using Cloud Run, Pub/Sub, and related managed services.
Quality & Reliability: Write clean, testable code and ensure solutions meet enterprise standards for security, observability, and operational readiness.
Collaboration: Work closely with cross-functional teams to refine requirements, review designs, and deliver production-grade solutions.

Must-Have Skills

Expert-level Python development skills, including experience with FastAPI or Flask and asynchronous programming.
Hands-on experience building GenAI applications using LangChain, LlamaIndex, LangGraph, or Google Vertex AI.
Practical experience working with vector databases such as Pinecone, Milvus, Weaviate, or pgvector.
Strong understanding of embeddings, similarity search, and RAG design patterns.
Experience deploying applications on Google Cloud Platform, including Cloud Run and Pub/Sub.
Solid understanding of REST APIs, system integration, and secure service design.
Experience working in Agile, cross-functional engineering teams.

Nice-to-Have Skills

Experience building agentic or multi-agent systems in production environments.
Familiarity with telecom domains such as OSS/BSS, network inventory, or automation platforms.
Experience with CI/CD pipelines, DevOps practices, or Infrastructure as Code.
Exposure to security, compliance, or regulated enterprise environments.

Inclusion & Diversity at Zinkworks

At Zinkworks, we are deeply committed to fostering a culture of diversity, inclusion, and belonging. We believe that our strength lies in the unique backgrounds, perspectives, and experiences of our team members. By embracing an inclusive environment, we empower innovation and collaboration across all levels of our organisation. Based in Ireland, we are proud to support and engage with our local communities through meaningful initiatives that promote equity and opportunity. Our commitment extends beyond the workplace, as we actively contribute to creating a more inclusive and connected society for all.