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Added 12 hours ago
H
Senior Electrical Engineer
HDR
Toronto, ON · Ottawa, ON · Richmond Hill, ON · Victoria, BC · Vancouver, BC · Calgary, AB
- Full-time
…environment. This isn’t just a job, it’s a chance to lead innovation, engineer impact, and build a legacy of…
Added 22 hours ago
O
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Toronto, ON · Greater Toronto Area, Canada
- $90,000 to $100,000 CAD / year
- Full-time
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Added 1 day ago
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Added 1 day ago
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ET
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Added 1 day ago
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AI Engineer
Altitude Technology Solutions Inc
Toronto, ON
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…orchestration, policy enforcement) following MCP protocol. Engineer robust guardrails for safety, compliance, and least-privilege…
Added 1 day ago
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Added 2 days ago
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Added 2 days ago
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Added 3 days ago
Software Developer Sr (AI Platform & Applications)
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Added 3 days ago
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Added 3 days ago
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Functional Safety Engineer/Verification and Validation
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Added 3 days ago
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Altitude Technology Solutions Inc

AI Engineer

Toronto, ON, Canada

Contract

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Job details

Job type: Contract
Apply by: Nov 22, 2026
Posting language: English
Posted: Oct 23, 2026

Original job description

Hello,

Greetings,

Hope you are safe & healthy.

My name is Kundan Mishra. I am a Technical Recruiter with Altitude Technology Solutions (ATS) INC.

The purpose of this email is to serve as an invitation to discuss the opportunity below with our customer that I think you or your candidate would be a great fit for.

Position: AI Engineer

Location: Toronto, Canada (3 days-Hybrid)

Exp- 10+ years

Must be able to Share Both Side of Driving License Copy

Must have good communication skills and should be confident

Job Description:

Build agentic AI systems: Design and implement tool-calling agents that combine retrieval, structured reasoning, and secure action execution (function calling, change orchestration, policy enforcement) following MCP protocol. Engineer robust guardrails for safety, compliance, and least-privilege access.
Productionize LLMs: Build evaluation framework for open-source and foundational LLMs; implement retrieval pipelines, prompt synthesis, response validation, and self-correction loops tailored to production operations.
Integrate with runtime ecosystems: Connect agents to observability, incident management, and deployment systems to enable automated diagnostics, runbook execution, remediation, and post-incident summarization with full traceability.
Collaborate directly with users: Partner with production engineers, and application teams to translate production pain points into agentic AI roadmaps; define objective functions linked to reliability, risk reduction, and cost; and deliver auditable, business-aligned outcomes.
Safety, reliability, and governance: Build validator models, adversarial prompts, and policy checks into the stack; enforce deterministic fallbacks, circuit breakers, and rollback strategies; instrument continuous evaluations for usefulness, correctness, and risk.
Scale and performance: Optimize cost and latency via prompt engineering, context management, caching, model routing, and distillation; leverage batching, streaming, and parallel tool-calls to meet stringent SLOs under real-world load.
Build a RAG pipeline: Curate domain-knowledge; build data-quality validation framework; establish feedback loops and milestone framework maintain knowledge freshness.
Raise the bar: Drive design reviews, experiment rigor, and high-quality engineering practices; mentor peers on agent architectures, evaluation methodologies, and safe deployment patterns

ESSENTIAL SKILLS

5+ years of software development in one or more languages (Python, C/C++, Go, Java); strong hands-on experience building and maintaining large-scale Python applications preferred.
3+ years designing, architecting, testing, and launching production ML systems, including model deployment/serving, evaluation and monitoring, data processing pipelines, and model fine-tuning workflows.
Practical experience with Large Language Models (LLMs): API integration, prompt engineering, fine-tuning/adaptation, and building applications using RAG and tool-using agents (vector retrieval, function calling, secure tool execution).
Understanding of different LLMs, both commercial and open source, and their capabilities (e.g., OpenAI, Gemini, Llama, Qwen, Claude).
Solid grasp of applied statistics, core ML concepts, algorithms, and data structures to deliver efficient and reliable solutions.
Strong analytical problem-solving, ownership, and urgency; ability to communicate complex ideas simply and collaborate effectively across global teams with a focus on measurable business impact.
Preferred: Proficiency building and operating on cloud infrastructure (ideally AWS), including containerized services (ECS/EKS), serverless (Lambda), data services (S3, DynamoDB, Redshift), orchestration (Step Functions), model serving (SageMaker), and infra-as-code (Terraform/CloudFormation).

Thanks & Regards

Kundan Mishra

Sr. Technical Recruiter

k.mishra@atsitinc.com

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More about this job

Responsibilities

Design, build, and productionize secure agentic AI systems and RAG pipelines, integrating them with observability, incident management, and deployment systems for diagnostics and remediation. Establish safety, governance, evaluation, reliability, and performance practices while collaborating with production and application teams to deliver measurable outcomes.

Requirements

Requires 10+ years of experience, including at least five years of software development and three years designing and launching production ML systems. Candidates should have hands-on LLM, RAG, and tool-using agent experience, strong programming and ML fundamentals, and effective communication and collaboration skills; AWS experience is preferred.

Skills

Python
Large Language Models
Agentic AI
Retrieval-Augmented Generation
Machine Learning
Production ML Systems
Prompt Engineering
Function Calling
Vector Retrieval
Model Evaluation
Model Deployment
AWS
Terraform
Data Processing Pipelines
Applied Statistics
Cloud Infrastructure

Visa sponsorship

Not detected in the job text

Hiring contact

Kundan Mishra

Hiring contact email

k.mishra@atsitinc.com

Keywords

Agentic AI
Model Context Protocol
Large Language Models
OpenAI
Gemini
Llama
Qwen
Claude
Retrieval-Augmented Generation
Vector Retrieval
Function Calling
Prompt Engineering
Model Fine-Tuning
Model Evaluation
Model Serving
Python
C/C++
Go
Java
AWS
ECS
EKS
Lambda
S3
DynamoDB
Redshift
Step Functions
SageMaker
Terraform
CloudFormation

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