Posted 4 months ago
Jr.Gen AI Engineer
@ KData Inc.
Ontario
Overview
KData Inc. is hiring a Junior Generative AI Engineer in Brampton on a contract basis to design, build and deploy agentic AI applications, AI agents and RAG-based systems, integrated with enterprise data platforms. The role requires 2+ years of software, data or AI engineering experience and strong Python and SQL skills.
Responsibilities:
- Design, develop and deploy agentic AI applications and AI agents
- Implement RAG, prompt engineering and AI workflow automation
- Integrate AI solutions with enterprise data platforms
- Support production deployment, monitoring and troubleshooting
Requirements summary:
- 2+ years in software, data or AI engineering
- Strong Python and SQL skills
- Experience with LLMs, RAG, vector search and embeddings
- Preferred: Google Cloud, Vertex AI or Databricks experience
Tools & skills
Source and dates
Source type not verified · zoho
- Employer posting date
- 2026-07-14
- First seen by our source
- 2026-10-12
- Source record updated
- 2026-10-12
These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.
Job details
| Seniority | Entry level |
| Department | Software development |
| Experience | 2+ years |
| Work setting | Office |
| Position | Mostly sitting |
| Physical demands | physical low · computer high |
| Languages | English |
| Education | Bachelor’s degree (required) |
| Fields of study | Computer Science, Software Engineering, Data Science, Artificial Intelligence, Information Technology |
Summary and details written by AI from the posting; the employer’s posting is the authority.
KData Inc.
| Field | Value |
|---|---|
| Open jobs on Jobsy | 4 |
Junior Generative AI Engineer (2+ Years Experience)
About the Role
We are looking for a motivated Junior Generative AI Engineer to join our team in Brampton. In this role, you will help design, develop, and deploy agentic AI-powered applications, AI agents, and RAG-based systems. You will play a key role in integrating GenAI technologies with our enterprise data platforms, ensuring solutions are robust, safe, and deliver real business value.
Key Responsibilities
AI Engineering
- Design, develop, test, and deploy Agentic AI-powered applications and AI agents.
- Build and enhance Generative AI and machine learning solutions that deliver business value.
- Implement Retrieval Augmented Generation (RAG), prompt engineering, and AI workflow automation patterns.
- Develop reusable APIs, services, and components to accelerate AI delivery.
Data & Platform Integration
- Integrate AI solutions with enterprise applications, data platforms, and business processes.
- Develop and optimize data pipelines and services that support AI applications.
- Contribute to enterprise AI platforms including Gemini Enterprise, Vertex AI, Databricks, and related technologies.
Governance & Operations
- Apply AI governance, security, privacy, and Responsible AI standards.
- Support production deployment, monitoring, troubleshooting, and continuous improvement of AI solutions.
- Document technical designs and collaborate with cross-functional teams to ensure successful delivery.
Requirements
Education & Experience
- Bachelor’s degree in Computer Science, Software Engineering, Data Science, Artificial Intelligence, Information Technology, Engineering, or a related field (equivalent experience considered).
- Google Cloud, Vertex AI, ML Engineer, Data Engineer, or related cloud / AI certifications.
- Experience building enterprise copilots, chatbots, document intelligence solutions, workflow assistants, or agentic applications.
- Experience implementing observability, quality evaluation, red-teaming, hallucination mitigation, and safety controls for AI systems.
- 2+ years of experience in software engineering, data engineering, machine learning engineering, AI engineering, or related technology delivery roles.
Technical Skills
- Strong programming skills in Python and SQL; experience with APIs, Git, CI/CD, testing, and software engineering practices.
- Experience with Generative AI, LLMs, RAG, vector search, embeddings, prompt engineering, agents, and model evaluation.
- Experience with Google Cloud Platform, Vertex AI, Gemini Enterprise, or comparable cloud AI platforms is preferred.
- Experience with Databricks, Spark / PySpark, Delta Lake, Unity Catalog, MLflow, and modern lakehouse patterns is preferred.
- Familiarity with AI frameworks and tools such as LangChain, LangGraph, CrewAI, AutoGen, FastAPI, Streamlit, Docker, Kubernetes, or related technologies is an asset.
- Understanding of data governance, data quality, metadata, lineage, security, privacy, and Responsible AI practices.
Soft Skills
- Strong problem-solving skills with the ability to translate business needs into practical, scalable engineering solutions.
- Clear communication skills, including the ability to explain AI concepts, risks, limitations, and trade-offs to technical and non-technical stakeholders.
- Demonstrated ownership mindset with a focus on delivery, production reliability, documentation, and continuous improvement.
- Ability to work collaboratively across data, AI, platform, cybersecurity, governance, architecture, business, and vendor teams.
- Curiosity and a learning mindset to keep pace with emerging AI technologies while applying sound enterprise judgment.
Journal
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