Jobs in Canada

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Added 1 month ago
A
Senior Data Scientist - AI/ML
Akkodis
Toronto, ON
- Contract
Enhance AI systems with reasoning capabilities, tool usage, and workflow automation.
Added 1 month ago
T
GenAI Prompt Engineer
TechDoQuest
Toronto, ON
- Contract
-Experience with automation frameworks and test scripting.
Added 1 month ago
TN
Software Development Lead
The North West Company
Winnipeg, MB
- Full-time
…applications, APIs, integrations, databases, and data-driven solutions, with hands-on experience in Python, C#, .NET, PL/SQL, T-SQL, Oracle, and Microsoft SQL…
Added 1 month ago
AC
Data Solutions Analyst
Air Canada
Dorval, QC
- Full-time
Ensure alignment with enterprise data governance frameworks and standards.
Added 1 month ago
B
Senior Manager, Data Engineer, Applied AI Data Ingestion & Integration
BMO
Toronto, ON · FCP
- Full-time
…and AI solutions. Our team combines engineering excellence with cutting-edge AI to deliver scalable, secure, and responsible solutions that power business innovation across the bank. We are…
Added 1 month ago
KG
Senior Platform Engineer
Kinross Gold Corporation
Toronto, ON
- Full-time
…ecosystem spanning on-premises datacenters, cloud platforms, automation frameworks, observability tooling, and enterprise integrations.This role combines platform engineering, cloud…
Added 1 month ago
Agentic AI Architect, Kitchener, ON ( Hybrid)
Siemens
Kitchener, ON
Collaborate with DevOps on CI/CD, deployment automation, and cloud/on-prem infrastructure design
Added 1 month ago
CL
Senior Cloud DevOps Engineer
Charger Logistics Inc.
Brampton, ON
- Full-time
Strong Python programming with PowerShell/Bash experience.
Added 1 month ago
IG
Machine Learning Engineer
IMCS Group
ON · Ontario, Canada
- Contract
Work Model: Hybrid – 2 days per week in-person at Toronto office preferred
Added 1 month ago
S
Application Developer
Systematix
Toronto, ON
- Contract
This role is Hybrid, 2 days per week onsite in downtown Toronto · Remote Work: 2 days per week in the office
Added 1 month ago
M(
[C] Full Stack Developer
MLSE (Maple Leaf Sports & Entertainment Partnership)
Toronto, ON · Scotiabank Arena
- Part-time
MLSE Sport Performance Lab is seeking a Full Stack Developer to join our team. This individual will play a key role in developing and maintaining team coaching applications across multiple…
Added 1 month ago
L
QA Engineer
Luxoft
Toronto, ON
- Contract
Hands-on experience with test automation frameworks (e.g., Selenium, Pytest, or similar)
Added 1 month ago
Product Security Engineer
Asana
Vancouver, BC
…member of our security engineering team, partnering directly with product and infrastructure teams to ensure we design and ship secure software. You will be instrumental in scaling our…
Added 1 month ago
F
Technical Consultant (Data & AI)
Fastloop
Vancouver, BC
- Full-time
Agentic Frameworks: Hands-on with Google ADK, LangChain, or LlamaIndex.
Added 1 month ago
A
Forward Deployed Engineer – AI, Data Engineering & MLOps / Toronto, ON (Onsite) - FTE
AceStack
Toronto, ON
- Full-time
We are seeking an experienced Forward Deployed Engineer with strong expertise in Python, PySpark, SQL, Claude, APIs, AI application development, and MLOps. The ideal candidate will work…
Added 1 month ago
Senior Internal Auditor
Twilio
BC
…that no matter your location, you’re part of a vibrant team with diverse experiences making a global impact each day. As we continue to revolutionize how the world interacts, we’re…
Added 1 month ago
SS
Product Security Specialist II
Safe Software
Remote, Canada
- $102,000 to $115,000 CAD / year
- Full-time
- Remote
Proficiency in Python for automation, tooling, or analysis.
Added 1 month ago
TI
CyberSecurity Specialist
Themesoft Inc.
Toronto, ON · North York, ON
- Contract
Experience with LLMs, AI agents, tool calling, orchestration frameworks, APIs, and security automation
Added 1 month ago
RE
Applied AI Engineer
Randstad Enterprise
Montreal, QC
- Contract
Hands-on experience with one or more AI development frameworks, such as LangGraph, LangChain, Claude Code SDK, OpenAI SDK, or similar technologies.
Added 1 month ago
TC
Forward deployed Engineer
Tata Consultancy Services
Toronto, ON · Greater Toronto Area, Canada
- $100,000 to $120,000 CAD / year
- Full-time
Hands-on experience with Git, Docker, Kubernetes, Airflow, MLflow, CI/CD, and distributed data processing frameworks.
Added 1 month ago
TC
Forward deployed Engineer
Tata Consultancy Services
Toronto, ON
- $100,000 to $120,000 CAD / year
- Full-time
Hands-on experience with Git, Docker, Kubernetes, Airflow, MLflow, CI/CD, and distributed data processing frameworks.
Added 1 month ago
GF
Data Analyst
Greenstone Financial Services Canada
Toronto, ON · North York, ON
- $70,000 to $80,000 CAD / year
- Full-time
Hybrid role – 3 days in office and 2 days work-from-home
Added 1 month ago
P
AI Intern, Applied & Agentic AI (December 2026 to April 2027)
ProCogia
Vancouver, BC
- $23 CAD / hour
Experiment with emerging tools and frameworks across AI agents, orchestration, retrieval, and model evaluation.
Added 1 month ago
B
Manager, Wealth Reporting Analytics & Automation
BMO
Toronto, ON
- Full-time
The Wealth Reporting Analytics and Automation understands and articulates the business case of business questions and the estimated value being delivered. Develops analytical and reporting…
Added 1 month ago
BI
DevOps & Cloud Systems - Fullstack Developer
BrightOrder Inc.
Remote, Canada
- Full-time
- Remote
We’re looking for a Full Stack Developer with strong DevOps and AWS experience to help build, automate, and scale BrightOrder’s cloud-based platform.

AceStack

Forward Deployed Engineer – AI, Data Engineering & MLOps / Toronto, ON (Onsite) - FTE

Toronto, ON, Canada

Full-time

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Job details

Job type: Full-time
Posting language: English
Posted: Oct 9, 2026

Original job description

Job Title: Forward Deployed Engineer – AI, Data Engineering & MLOps

Location: Toronto, ON

Work Mode: Onsite

Experience: 10–14 Years

Job Description

We are seeking an experienced Forward Deployed Engineer with strong expertise in Python, PySpark, SQL, Claude, APIs, AI application development, and MLOps. The ideal candidate will work directly with client stakeholders and engineering teams to discover business problems, analyze real-world data, rapidly build AI-powered solutions, and deploy reliable, production-ready applications that deliver measurable business outcomes.

Must-Have Technical Skills

Python, PySpark & SQL: Strong hands-on experience in data engineering, data profiling, distributed processing, and production-grade software development.
AI & LLM Engineering: Experience with Claude, prompt engineering, Retrieval-Augmented Generation (RAG), vector databases, semantic search, and agentic AI workflows.
APIs & Application Integration: Expertise in REST APIs, FastAPI, enterprise application integration, and connecting AI solutions to enterprise data sources.
Data Engineering & DataOps: ETL/ELT, batch and streaming pipelines, data quality, metadata, lineage, orchestration, and observability.
MLOps / LLMOps: Model lifecycle management, MLflow, CI/CD, automated deployment, model evaluation, monitoring, rollback, and production support.
Cloud & Platform Engineering: Experience with cloud data platforms, Docker, Kubernetes, Airflow, Git, distributed computing, and infrastructure automation.
Security & Governance: IAM/RBAC, encryption, secrets management, data privacy, auditability, compliance, and responsible AI controls.
Production Engineering: Automated testing, performance optimization, error handling, reliability engineering, incident resolution, and operational monitoring.
Data Discovery & Evaluation: Profiling unfamiliar datasets, assessing data quality and feasibility, building evaluation datasets, conducting error analysis, and improving AI solution quality.
Forward-Deployed Delivery: Experience working directly with clients to conduct discovery, build rapid prototypes, integrate enterprise systems, deploy solutions, and measure business impact.

Roles & Responsibilities

Engage directly with client SMEs, business users, product owners, and engineering teams to understand workflows, business objectives, data sources, constraints, and success criteria.
Design, develop, and deploy enterprise-grade AI and data applications using Python, PySpark, SQL, Claude, FastAPI, and REST APIs.
Profile and analyze client data to assess data quality, coverage, volumes, distributions, edge cases, and business-process gaps.
Build and operationalize Claude-powered applications, copilots, RAG pipelines, vector search solutions, and agentic AI workflows.
Architect and implement scalable batch, streaming, and real-time data pipelines across enterprise data platforms.
Rapidly develop prototypes using real client data and APIs, validate them with users, and iteratively harden solutions for production.
Implement MLOps/LLMOps workflows covering evaluation, automated testing, CI/CD, deployment, monitoring, rollback, and lifecycle management.
Establish responsible AI, security, privacy, traceability, governance, and human-oversight controls.
Troubleshoot data-access, API, identity, networking, infrastructure, security, and deployment issues in collaboration with client teams.
Own post-deployment stabilization, incident diagnosis, performance and latency optimization, cost monitoring, and production support.
Measure adoption and business outcomes using KPIs such as productivity gains, time saved, error reduction, processing efficiency, and solution quality.
Lead technical workshops, solution design, architecture reviews, code reviews, demonstrations, and effort estimation.
Develop reusable frameworks, accelerators, reference architectures, runbooks, and implementation standards.
Mentor engineering teams and ensure effective knowledge transfer, documentation, operational handover, and ongoing support readiness.

Qualifications

Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Management, or a related discipline; equivalent relevant experience may be considered.
10–14 years of relevant experience across data engineering, AI application development, cloud data platforms, APIs, and production software engineering.
Experience delivering solutions in Banking, Financial Services, Insurance (BFSI), or other regulated enterprise environments.
Strong client-facing consulting, problem-solving, communication, and technical presentation skills.
Demonstrated ability to take solutions from discovery and rapid prototyping through production deployment, adoption, and measurable business outcomes.
Willingness to work onsite with client teams and travel when required.

Preferred: Certifications in cloud platforms, AI engineering, MLOps, data engineering, Kubernetes, enterprise architecture, or security.

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More about this job

Responsibilities

Engage with client stakeholders to discover business needs, analyze data, and design, prototype, deploy, and support production-grade AI and data applications. Build scalable data pipelines and Claude-powered solutions, operationalize MLOps/LLMOps, establish security and governance controls, and measure business outcomes.

Requirements

Requires 10–14 years of relevant experience across data engineering, AI application development, cloud data platforms, APIs, and production software engineering, along with strong client-facing consulting and communication skills. A bachelor’s degree or equivalent relevant experience is required; experience in BFSI or other regulated enterprise environments is expected, and relevant certifications are preferred.

Skills

Python
PySpark
SQL
Claude
Prompt Engineering
Retrieval-Augmented Generation
Vector Databases
Semantic Search
Agentic AI
REST APIs
FastAPI
Data Engineering
MLOps
LLMOps
Cloud Platforms
Kubernetes

Visa sponsorship

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Keywords

Python
PySpark
SQL
Claude
Prompt Engineering
Retrieval-Augmented Generation
Vector Databases
Semantic Search
Agentic AI
REST APIs
FastAPI
ETL/ELT
Batch and Streaming Pipelines
DataOps
MLOps
LLMOps
MLflow
CI/CD
Docker
Kubernetes
Airflow
Cloud Data Platforms
Distributed Computing
Data Governance
Responsible AI
BFSI
Data Quality
Model Evaluation
Production Support
Infrastructure Automation

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Jobs in Canada