Jobs in Canada

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Added 28 days ago
R&
Senior Delivery Manager
Robots & Pencils
Canada
- Full-time
Help implement the AI Development Life Cycle (AIDLC) across your engagements, and set the standard other delivery managers follow for standing it up
Added 28 days ago
KG
Forward Deployed Engineer (Python/PySpark, LLM)
K&K Global Talent Solutions INC.
Toronto, ON
- Full-time
…solutions. The ideal candidate combines strong data engineering and software development skills with practical experience in Claude-powered AI applications, RAG, Agentic AI, cloud…
Added 28 days ago
Principal Platform Architect – Physical AI Data & Runtime Platform, Kitchener, ON
Siemens
Kitchener, ON
Are you a senior software architect passionate about designing scalable platforms for AI, robotics, industrial data, and execution-oriented applications?
Added 28 days ago
CL
Senior AI Engineer
Charger Logistics Inc.
Brampton, ON
- Full-time
…team based out of our Brampton office and contribute to the development of AI-driven solutions for various departments. This role focuses on building production AI agents and MCP (Model…
Added 28 days ago
RB
Director, Product Strategy & Roadmap
Royal Bank of Canada
Toronto, ON
- Full-time
Experience building developer platforms, APIs, or self-service builder tools
Added 28 days ago
R
Data Scientist III
Raise
Toronto, ON
- Full-time
Break down broader data science development milestones into actionable goals, activities, and work plans
Added 28 days ago
Senior Data Engineer
Clutch Technologies Inc.
Toronto, ON
Use AI as part of your everyday engineering workflow to prototype, accelerate development, and improve code quality.
Added 28 days ago
R
Data Scientist I
Raise
Toronto, ON
- Full-time
Break down broader data science development milestones into actionable goals, activities, and work plans
Added 28 days ago
G
Gen AI Developer
Galent
Halifax, NS
- Contract
Advanced Python proficiency with strong software engineering fundamentals (version control, testing, code reviews)
Added 28 days ago
M
Senior Data Engineer, Retirement Operations
Manulife
Toronto, ON · Montreal, QC · Halifax, NS
- Full-time
Evaluates, integrates, and manages tools and frameworks within the data engineering ecosystem, ensuring compatibility and efficiency in model development and deployment.
Added 28 days ago
Data and AI Engineer
Scotiabank
Toronto, ON
Advanced Python and SQL skills with strong software design, API development, and testing practices.
Added 28 days ago
RA
Senior Data Scientist (Machine Learning & Generative AI)
Recrute Action
Toronto, ON
- Contract
Break down broader data science development milestones into actionable goals, activities, and work plans.
Added 28 days ago
P
Technical Product Manager
PostGrid
Toronto, ON · Greater Toronto Area, Canada
- Full-time
Bachelor's in Computer Science, Software Engineering, or a related field (or equivalent practical experience)
Added 28 days ago
AI Full Stack Engineer
Scotiabank
Toronto, ON
Experience applying secure software development practices, access controls, secrets management, and production operational controls.
Added 28 days ago
KG
Environmental Coordinator
Kinross Gold Corporation
Red Lake, ON
- Full-time
The Great Bear project is a development-stage asset located in the renowned and prolific Red Lake mining district, and represents one of the most exciting recent gold discoveries globally.…
Added 28 days ago
RB
Senior Director, AI Product Management
Royal Bank of Canada
Toronto, ON
- Full-time
Background in platform engineering or developer experience teams
Added 28 days ago
TC
Data & Analytics Solution Architect
Tata Consultancy Services
Toronto, ON · Greater Toronto Area, Canada
- $120,000 to $150,000 CAD / year
- Full-time
Mentor architects and engineers and contribute to capability development, technical assessments, and knowledge-sharing initiatives.
Added 28 days ago
T
Software Engineer, AI/ML Infrastructure
Thumbtack
Remote, Canada
- Full-time
- Remote
As a Software Engineer on the ML Infrastructure team, you will work closely with product and platform engineering teams to build and evolve core AI platform capabilities. You will help…
Added 28 days ago
R|
Programmer
RI-MUHC | Research Institute of the MUHC | #rimuhc
Montreal, QC
- Full-time
Department / Research Program: CVIS/IDIGH (MLOps & AI Development)
Added 28 days ago
E
Sr. Data Scientist
Eneon-ES
Toronto, ON · Greater Toronto and Hamilton Area, ON
- Full-time
Lead end-to-end data science work (preprocessing, EDA, feature engineering, model development, training, and evaluation)
Added 28 days ago
P
Machine Learning Engineer
Point11
Toronto, ON · Greater Toronto Area, Canada
- Full-time
An annual learning budget for conferences and development
Added 28 days ago
MI
Project Engineer
Magna International
Brampton, ON
- Full-time
· Able to work overtime, including afternoon, evening shifts and weekends as required · Must have valid passport and driver’s license
Added 28 days ago
ZS
Python Full-stack Developer
Zodiac Solutions, Inc
Toronto, ON
- Full-time
Knowledge of design patterns & best practices in software development
Added 28 days ago
ZS
Core Java Developer with E-trade Experience
Zodiac Solutions, Inc
Toronto, ON
- Full-time
We are seeking a highly skilled Senior Java Developer with AI experience to join the FIC Global Spread Products eTrading Technology team. The successful candidate will contribute to the…
Added 28 days ago
RA
Data Scientist I – GenAI & Machine Learning
Recrute Action
Toronto, ON
- Contract
Bring your passion for data, machine learning, and GenAI to the insurance sector for our client. Support the development of practical, innovative solutions while contributing to advanced…

K&K Global Talent Solutions INC.

Forward Deployed Engineer (Python/PySpark, LLM)

Toronto, ON, Canada

Full-time

Apply on LinkedIn About employer

Applications open in a new tab.

Job details

Job type: Full-time
Apply by: Nov 13, 2026
Experience: 10+ years of experience in Data Engineering, AI Application Development, Cloud Data Platforms, and Production-grade Software Engineering.
Posting language: English
Posted: Oct 14, 2026

Original job description

Position: Forward Deployed Engineer (Python/PySpark, LLM)

Location: Toronto, ON (Hybrid)

Employment Type: Full Time

Experience Required: 10 + Years

Role Summary:

We are seeking a hands-on Senior AI & Data Engineering professional to design, build, deploy, and support enterprise-grade AI and data solutions. The ideal candidate combines strong data engineering and software development skills with practical experience in Claude-powered AI applications, RAG, Agentic AI, cloud platforms, and production-grade MLOps/LLMOps. This role requires close client collaboration, rapid prototyping, technical leadership,

and accountability for measurable business outcomes.

Must-Have Technical Skills:

10+ years of experience in Data Engineering, AI Application Development, Cloud Data Platforms, and Production-grade Software Engineering.
Strong hands-on expertise in Python, PySpark, SQL, REST APIs, FastAPI, and enterprise application integration.
Experience designing and building AI-powered applications using Claude, Prompt Engineering, Retrieval-Augmented Generation (RAG), Vector Databases, Semantic Search, and Agentic AI patterns.
Deep understanding of Data Engineering frameworks, including ETL/ELT, batch and streaming pipelines, data quality, metadata management, lineage, observability, and DataOps practices.
Experience implementing and operationalizing MLOps / LLMOps capabilities including model lifecycle management, CI/CD pipelines, MLflow, monitoring, deployment automation, rollback, and production support.
Strong knowledge of cloud and modern data platforms, including compute, storage, integration, orchestration, security, networking, monitoring, and cost optimization services.
Hands-on experience with Git, Docker, Kubernetes, Airflow, MLflow, CI/CD, and distributed data processing frameworks.
Strong understanding of enterprise security and governance principles, including IAM/RBAC, encryption, secrets management, privacy controls, auditability, compliance, and secure data access.
Ability to translate business requirements into scalable solution designs, define non-functional requirements, estimate effort, and drive production-ready implementation.
Experience working with Banking, Financial Services, or Insurance (BFSI) data environments and familiarity with regulatory, security, privacy, and resilience requirements.
Strong client-facing consulting skills with experience conducting discovery workshops, solution shaping, rapid prototyping, stakeholder communication, and technical presentations.
Bachelor’s degree in computer science, Engineering, Information Systems, Data Management, or a related discipline.
Preferred certifications in Cloud Platforms, Kubernetes, AI Engineering, MLOps, Data Engineering, Enterprise Architecture, Security, or Program Delivery.
Experience working in a forward-deployed delivery model by embedding with client SMEs, business users, and engineering teams through solution validation, production deployment, adoption, and handover.
Strong hands-on data discovery skills, including profiling unfamiliar client data with Python, pandas, PySpark, and SQL; assessing coverage and quality; and quantifying volumes, distributions, edge cases, and business-process gaps before development.
Ability to rapidly build thin working solutions using real client data and APIs, validate them with users, and iteratively harden them with automated tests, security controls, error handling, observability, and production support procedures.
Experience creating business-relevant evaluation datasets with client SMEs, measuring ML or LLM quality, performing structured error analysis, grouping failures by root cause, and prioritizing improvements across releases.
Demonstrated production ownership after go-live, including monitoring, incident diagnosis, rollback, stabilization, performance and latency troubleshooting, and resolution of user-reported issues.
Ability to measure user adoption and business impact after launch using usage data and agreed KPIs such as time saved, error reduction, straight-through processing, quality improvement, or productivity gains.

Key Responsibilities:

Design, develop, and deploy enterprise-grade AI and data applications using Python, PySpark, Claude, SQL, APIs, and modern cloud-based data platforms.
Engage with business and technology stakeholders to understand business objectives, data landscape, functional requirements, non-functional requirements, and delivery expectations.
Define solution architecture, implementation roadmaps, and technical approaches that align with business goals and operational requirements.
Architect scalable data platforms, data pipelines, and AI solutions with a strong focus on performance, security, reliability, and cost optimization.
Develop batch, real-time, and streaming data processing solutions integrating multiple enterprise data sources and downstream applications.
Build and operationalize Claude-powered applications, copilots, and AI workflows using prompt engineering, Retrieval-Augmented Generation (RAG), vector search, and enterprise data integration.
Implement responsible AI practices, including governance, security, privacy, traceability, validation, and human oversight controls.
Design and enforce engineering standards, reusable frameworks, CI/CD practices, infrastructure automation, and production deployment patterns.
Provide technical leadership across solution design, code reviews, architecture reviews, testing, deployment, and production support activities.
Drive platform reliability, performance tuning, observability, incident resolution, and operational excellence across data and AI workloads.
Collaborate closely with architects, data engineers, AI specialists, platform teams, and client stakeholders to deliver production-ready solutions.
Support solutioning, RFP responses, technical demonstrations, effort estimation, and client workshops for new opportunities.
Develop reusable accelerators, reference architectures, implementation playbooks, and engineering best practices to improve delivery efficiency.
Mentor engineering teams and contribute to hiring, capability development, technical assessments, and knowledge-sharing initiatives.
Embed with client SMEs, product owners, and engineers for a defined, time-bound outcome; map the workflow, users, data, constraints, and decision points; and agree on the first useful release and measurable success criteria.
Analyze client data early to assess coverage, quality, volumes, distributions, edge cases, and process feasibility before committing to solution design and build scope.
Build a thin working version quickly on real data and APIs, validate it with business users, and harden it iteratively for security, reliability, maintainability, and production operations.
Create evaluation datasets with client SMEs, perform model and LLM error analysis. and suggest improvements.
Resolve data-access, API, identity, network, security, infrastructure, and deployment blockers in partnership with client data, platform, security, and engineering teams.
Own post-go-live stabilization by monitoring services, diagnosing user-reported failures, latency and cost issues, executing rollback or recovery where required, and shipping fixes.
Measure adoption and realized business impact using usage data and agreed KPIs, and communicate results through concise dashboards, demonstrations, or executive summaries.
Complete structured handover with runbooks, support ownership, knowledge transfer, and reusable components, test documents, and deployment patterns.

Preferred Background:

Strong problem-solving and decision-making abilities with a balanced focus on business outcomes, technology strategy, security, scalability, and operational excellence.
Excellent communication, presentation, and stakeholder management skills, with the ability to engage effectively with business, technical, and executive audiences.
Strong consulting mindset with the ability to analyze complex challenges, recommend practical solutions, and clearly articulate architectural trade-offs.
Proven ability to lead and influence cross-functional, distributed teams in a collaborative and fast-paced delivery environment.
High level of ownership, accountability, attention to detail, and commitment to engineering quality and delivery excellence.
Strong planning, prioritization, and multitasking skills with the ability to manage multiple initiatives, stakeholders, and delivery commitments simultaneously.
Ability to mentor engineers and architects, foster knowledge sharing, and drive adoption of engineering best practices.
Adaptability and resilience to work effectively in rapidly evolving technologies, business priorities, and client environments.

Apply on LinkedIn About employer

More about this job

Responsibilities

Design, build, deploy, and support enterprise AI and data solutions, including data pipelines and Claude-powered applications, with a focus on security, reliability, performance, and cost. Work directly with client stakeholders from discovery through prototyping, production stabilization, impact measurement, and handover, while providing technical leadership and mentoring.

Requirements

Requires 10+ years of experience in data engineering, AI application development, cloud data platforms, and production software engineering, with hands-on expertise in Python, PySpark, SQL, APIs, RAG, and MLOps/LLMOps. A bachelor’s degree in a related discipline is required, along with strong client-facing consulting skills; BFSI experience and relevant technical certifications are preferred.

Skills

Python
PySpark
SQL
FastAPI
REST APIs
Claude
Prompt Engineering
Retrieval-Augmented Generation
Agentic AI
Vector Databases
Data Engineering
MLOps/LLMOps
Cloud Platforms
Kubernetes
Airflow
Client-Facing Consulting

Visa sponsorship

Not detected in the job text

Keywords

Python
PySpark
SQL
FastAPI
REST APIs
Claude
Prompt Engineering
Retrieval-Augmented Generation
Agentic AI
Vector Databases
Semantic Search
ETL/ELT
Batch Processing
Streaming Pipelines
DataOps
MLOps
LLMOps
MLflow
Docker
Kubernetes
Airflow
CI/CD
Cloud Data Platforms
Data Governance
IAM/RBAC
Banking, Financial Services, and Insurance
Data Quality
Observability
Model Evaluation
Production Support

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Jobs in Canada