Jobs in Canada

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Added 1 month ago
KG
DevOps Platform Engineer | AI & LLMOps Infrastructure
K&K Global Talent Solutions INC.
ON · Ontario, Canada
- Full-time
…foundational infrastructure that powers our next-generation developer platforms and autonomous AI/LLM agent frameworks. This is a highly specialized role bridging the gap between advanced…
Added 1 month ago
JG
FORWARD DEPLOYEMENT ENGINEER
J&M Group
Canada
- Full-time
Must Have Technical/Functional Skills
Added 1 month ago
Y
GenAI Prompt Engineer
Yochana
Toronto, ON
- Contract
Location – Brampton, ON or Toronto, ON (Onsite)
Added 1 month ago
AI
Automation Engineer- CMDB/Asset Management, Python, REST APIs
Astra-North Infoteck Inc. ~ Conquering today’s challenges, achieving tomorrow’s vision!
Calgary, AB
- Full-time
Onsite - 5 days in office (8:00 AM – 05:00 PM MST) · Top 3 Must Have Skills:
Added 1 month ago
T
Full Stack Engineer
TEEMA
Toronto, ON
- $70 to $75 CAD / hour
- Contract
Location: Toronto, ON – Hybrid, 3 days onsite per week
Added 1 month ago
A
Senior Data Scientist - AI/ML
Akkodis
Toronto, ON
- Contract
Work Model: Hybrid (3 days onsite per week, Thursday designated as team collaboration day)
Added 1 month ago
CI
Senior Autonomy Validation Specialist / Spécialiste senior de la validation de l’autonomie
Caterpillar Inc.
Laval, QC
- Full-time
This position requires the selected individual to work onsite at the Laval, QC office.
Added 1 month ago
E
Analyste QA senior, SDET – Tests de paiements, d’API et d’événements / Senior QA Analyst, SDET – Payments, API & Event Testing
Expleo
Montreal, QC
- Contract
Added 1 month ago
B
Technical Product Manager – Aviation Maintenance Data
Boeing
Vancouver, BC · Richmond, BC · CAN - Richmond, Canada
- Full-time
This position is hybrid. This means that the selected candidate will be required to perform some work onsite at Richmond location. This is at the hiring team’s discretion and could…
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
Specialist Systems, IT
City of Mississauga
Mississauga, ON
The role follows a hybrid work model, requiring employees to be onsite in the office 3 days per week and allowing remote work for the remaining days
Added 1 month ago
CO
Specialist Systems, IT
City of Mississauga
Mississauga, ON
- Full-time
The role follows a hybrid work model, requiring employees to be onsite in the office 3 days per week and allowing remote work for the remaining days
Added 1 month ago
B
Senior Data Scientist – Generative AI & Machine Learning
Bevertec
Toronto, ON
- Contract
Work Arrangement: Hybrid – 3 days onsite per week, including Thursday
Added 1 month ago
B
Junior Data Scientist
Bevertec
Toronto, ON
- Contract
Work Arrangement: Hybrid – 3 days onsite per week, including Thursday
Added 1 month ago
WT
Data Engineer
Wissen Technology
Montreal, QC
- Full-time
Mode of Work: Onsite 3-4 days per week
Added 1 month ago
V
Python Software Engineer
Varonis
Vancouver, BC · Greater Vancouver, BC
- Full-time
The Location: We are considering candidates who are able to work by onsite, located within physical proximity to Vancouver, Canada.
Added 1 month ago
LI
Enterprise Search Engineer
LanceSoft, Inc.
Toronto, ON
- Contract
The successful candidate will be working seven (7) hours per day, five (5) days per week based on normal working Business Hours
Added 1 month ago
GT
AML Developer
Global Technical Talent, an Inc. 5000 Company
Toronto, ON
- $85 to $103 CAD / hour
- Contract
Onsite Flexibility: Hybrid - 3 days in office, 2 days work from home (could potentially go to 4 days in office)
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
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Data Scientist
Hays
ON · Ontario, Canada
- $60 to $62 CAD / hour
- Contract
Proficient in Python for data science and GenAI application development
Added 1 month ago
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IT Support Analyst IV
TD
Toronto, ON
- Full-time
Knowledge of automation tools, frameworks, and languages such as Python and JSON, plus a foundational understanding of AI concepts.
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
Strong hands-on expertise in Python, PySpark, SQL, REST APIs, FastAPI, and enterprise application integration.
Added 1 month ago
TC
Forward deployed Engineer
Tata Consultancy Services
Toronto, ON
- $100,000 to $120,000 CAD / year
- Full-time
Strong hands-on expertise in Python, PySpark, SQL, REST APIs, Fast API, and enterprise application integration.
Added 1 month ago
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Member of Technical Staff 2 - AI
Nutanix
Vancouver, BC
- $103,000 to $155,000 CAD / year
- Full-time
Experience building applications with Go and Python
Added 1 month ago
RI
Senior Full Stack Engineer - Java /
Rose International
Mississauga, ON
- Full-time
Must Have Skills/Attributes: Angular, Artificial Intelligence (AI), Banking/Financial, Java, Kafka, Kubernetes, Microservices, Spring Boot

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

Not detected in the job text

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