AI &Intelligent Integration Developer

@ Zortech Solutions

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Canada

Contract7+ years experience

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SIGNALS

Overview

Zortech Solutions is hiring an AI and Intelligent Integration Developer on a contract basis to integrate enterprise AI platforms, LLMs and AI-powered services into business applications and workflows. The work covers RAG, AI agents, API-based AI integrations, and production support across APIs, cloud and event-driven systems. The posting requires 7+ years of enterprise API and integration experience, strong Java (Spring Boot) and Python skills, and GCP cloud experience.

Responsibilities:

Integrate enterprise AI platforms and LLMs into business applications
Build RAG, AI agent and API-based AI solutions
Troubleshoot APIs, integrations and cloud platforms
Support production deployments and root-cause analysis

Requirements summary:

7+ years enterprise API and microservices development
5+ years cloud-native development, preferably GCP
Strong Java (Spring Boot) and Python
Experience with AI platform integration and RAG or AI agents

Tools & skills

Apigee Kong MuleSoft Kafka Pub/Sub Kubernetes Docker Vertex AI Gemini GitHub Copilot

Source and dates

Source type not verified · apify-linkedin

Employer posting date: 2026-11-12
First seen by our source: 2026-11-14
Source record updated: 2026-11-14

These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.

Job details

Seniority	Senior
Department	Software development
Experience	7+ years
Travel	air: none · ground: none
Work setting	Office
Position	Mostly sitting
Physical demands	physical low · computer high
Languages	English

Summary and details written by AI from the posting; the employer’s posting is the authority.

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Zortech Solutions

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Field	Value
Open jobs on Jobsy	3

Job description

Job Description:

Integrate enterprise AI platforms, Large Language Models (LLMs), and AI-powered services into business applications and workflows.
Build AI-enabled solutions using technologies such as Vertex AI, Gemini, OpenAI, Anthropic Claude, or equivalent platforms.
Implement Retrieval-Augmented Generation (RAG), AI agents, intelligent workflows, and API-based AI integrations.
Leverage AI-assisted engineering tools to improve software development productivity and quality.
Collaborate with architecture, data, and AI teams to deliver scalable, secure, and responsible AI solutions.
Ensure AI integrations comply with enterprise security, governance, privacy, and Responsible AI standards.

Operational Excellence

Troubleshoot and resolve complex issues across APIs, integrations, cloud platforms, and event-driven systems.
Support production deployments, incident resolution, and root-cause analysis.
Optimize solution performance, scalability, reliability, and maintainability.
Contribute to reusable frameworks, engineering standards, and continuous improvement initiatives.

Experience

7+ years of hands-on experience developing enterprise APIs, microservices, and integration solutions.
Strong experience with Java (Spring Boot) and Python development.
Experience building event-driven and real-time integration solutions using Kafka and messaging technologies.
5+ years of experience developing and deploying cloud-native solutions, preferably on GCP.
Experience with API management platforms such as Apigee, Kong, MuleSoft, or equivalent technologies.
Strong knowledge of API security, OAuth, JWT, and secure software development practices.
Experience integrating enterprise AI platforms such as Vertex AI, Gemini, OpenAI, Anthropic Claude, Azure AI Services, or equivalent technologies.
Experience developing AI-enabled applications, RAG solutions, AI agents, or intelligent workflow automation.
Understanding of AI governance, security, privacy, and Responsible AI practices.

Technical Skills

Java (Spring Boot) and Python
APIs, RESTful services, microservices, and enterprise integration patterns
Apigee, Kong, MuleSoft, or similar API management platforms
Kafka, Pub/Sub, event-driven architecture, messaging, and real-time streaming
Kubernetes, Docker, and cloud-native application development
Google Cloud Platform (GCP), including Cloud Run, Cloud Functions, and Pub/Sub
OAuth, JWT, API security, and secure development practices
CI/CD, DevOps, and automation
Distributed systems, scalability, resiliency, monitoring, and observability
Vertex AI, Gemini, OpenAI, Anthropic Claude, Azure AI Services
Large Language Models (LLMs), prompt engineering, embeddings, and AI integration patterns
Retrieval-Augmented Generation (RAG), vector databases, AI agents, intelligent workflows, and MCP
AI-assisted development tools such as GitHub Copilot, Gemini CLI, and Cursor
AI governance, Responsible AI, security, privacy, and compliance