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Added 13 mins ago
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Amyantek

Senior AI Engineer

Toronto, ON, Canada
Greater Toronto Area, Canada, Canada

Job type: Contract
Apply by: Oct 28, 2026
Experience: 5+ years of software engineering, backend engineering, applied AI, or related experience
Posting language: English
Posted: Sep 28, 2026

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Applications open in a new tab.

Original job description

Please send your resume at anila.dada@amyantek.com if you are interested in this role.If you are not interested, please feel free to pass it in your network for anyone looking for work.

Senior AI Engineer – Production AI / LLM Applications

We are looking for a Senior AI Engineer to design, build, and deploy production-ready AI applications and AI agents for enterprise clients.

This role requires someone who combines strong AI/LLM expertise with real software engineering experience. You should be comfortable taking an AI use case from concept or prototype through architecture, development, testing, deployment, monitoring, and production support.

You may work with tools such as Claude, GitHub Copilot, OpenAI Codex, and enterprise data platforms such as Databricks to develop AI agents and applications for specific business processes and use cases.

Important: We are not looking for someone whose experience is primarily prompt engineering, prototypes, or "vibe coding." We need an engineer who understands how to turn AI prototypes into secure, reliable, maintainable, production-grade software.

What You’ll Do

Design and build production-grade AI applications and services using Python
Translate business requirements and AI use cases into practical technical solutions
Build AI agents, backend services, APIs, workflows, and integrations
Integrate LLMs and AI capabilities with enterprise applications and data platforms
Design evaluation frameworks and test cases to measure AI accuracy, quality, reliability, and consistency
Develop approaches to make probabilistic LLM-based systems more predictable and dependable
Implement observability, logging, tracing, instrumentation, and monitoring
Build reusable components for prompting, model interaction, evaluation, retrieval, and orchestration
Develop automated testing and CI/CD pipelines
Deploy and support AI applications in production environments
Troubleshoot production issues and improve application performance and reliability
Contribute to architecture and technology decisions
Establish engineering best practices for Python and AI application development
Work directly with clients and stakeholders to refine requirements and evaluate technical trade-offs

Must-Have Experience

5+ years of software engineering, backend engineering, applied AI, or related experience
Strong Python development skills
Experience building maintainable, production-grade Python applications
Proven experience taking AI/LLM applications beyond POC/prototype into production
Experience building backend services and APIs using Python
Strong software engineering fundamentals: modular architecture, testing, Git/version control, and CI/CD
Hands-on experience evaluating LLM outputs and creating repeatable AI test cases
Experience with production observability, logging, tracing, instrumentation, and monitoring
Understanding of the challenges involved in making probabilistic AI systems reliable
Experience integrating applications with APIs, enterprise data sources, and business systems
Strong problem-solving skills and ability to work beyond predefined frameworks
Strong client-facing and stakeholder communication skills
Ability to combine hands-on engineering with technical architecture and solution design

Nice-to-Haves

RAG, semantic search, embeddings, and vector databases
Agentic AI and multi-step LLM workflows
Structured LLM outputs, function/tool calling, and schema-driven AI applications
AI evaluation, experimentation, and observability platforms
Databricks
Microsoft Azure AI Foundry / Microsoft Fabric
Cloud infrastructure and containerization
Production deployment of Python services
Modern Python API, validation, testing, and dependency-management frameworks
Enterprise data platforms and semantic layers
Experience with Claude, GitHub Copilot, OpenAI Codex, or similar AI development tools
Consulting, financial services, manufacturing, or other enterprise experience
Experience supporting business-critical or external client-facing production applications

Ideal Candidate

You are not simply someone who can build an impressive AI demo. You understand software architecture, production deployment, testing, reliability, monitoring, security, and maintainability and can turn an AI concept into an enterprise-ready solution.

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More about this job

Responsibilities

Design, build, deploy, and support production-grade AI applications, agents, backend services, APIs, and integrations using Python and enterprise data platforms. Establish evaluation, testing, observability, and CI/CD practices while collaborating with clients and stakeholders on requirements, architecture, and technical trade-offs.

Requirements

Requires 5+ years of relevant engineering experience, strong Python and backend/API development skills, and experience taking AI/LLM applications from prototypes into production. Candidates should also have strong software engineering fundamentals, LLM evaluation and monitoring experience, and the ability to communicate with clients and stakeholders.

Skills

Python
Production AI Applications
Large Language Models
AI Agents
Backend Services
API Development
LLM Evaluation
Automated Testing
CI/CD
Observability
Logging And Monitoring
Software Architecture
RAG
Semantic Search
Vector Databases
Databricks

Visa sponsorship

Not detected in the job text

Hiring contact email

anila.dada@amyantek.com

Keywords

Python
Large Language Models
Production AI
AI Agents
Backend Services
APIs
Enterprise Applications
Databricks
Claude
GitHub Copilot
OpenAI Codex
LLM Evaluation
RAG
Semantic Search
Embeddings
Vector Databases
Agentic AI
Function Calling
Structured Outputs
Observability
Logging
Tracing
Monitoring
Automated Testing
CI/CD
Git
Microsoft Azure AI Foundry
Microsoft Fabric
Cloud Infrastructure
Containerization

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