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Added 8 mins ago
IG
Machine Learning Engineer
IMCS Group
ON · Ontario, Canada
- Contract
We are looking for a highly experienced Senior AWS SageMaker / MLOps Engineer with 6+ years of overall IT experience and strong expertise in building, deploying, and operationalizing…
Added 25 mins ago
SL
Principal Software Engineer, MarTech Platforms & Digital Enablement
Sun Life
Toronto, ON · Waterloo, ON · Sun Life Toronto Atria
- Full-time
Strong hands-on experience with: Java / Spring Boot / Python JavaScript / TypeScript APIs and Microservices Docker and Kubernetes
Added 25 mins ago
Dev Ops Engineer (Student Position)
The Canada Life Assurance Company
Toronto, ON
We are looking for a DevOps Engineer Student who is interested in learning how modern technology platforms are built, delivered, and supported within a large enterprise environment.
Added 25 mins ago
O
Conseiller(ère) en ingénierie de données sénior
Onepoint
Montreal, QC · Quebec, QC
- Full-time
Avoir réussi au moins 3 évaluations Microsoft Applied Skills directement en lien avec Fabric ou détenir la certification Microsoft Fabric Data Engineer Associate (DP-700);
Added 25 mins ago
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Conseiller(ère) en ingénierie de données sénior
Wepoint
Montreal, QC · Quebec, QC
- Full-time
Avoir réussi au moins 3 évaluations Microsoft Applied Skills directement en lien avec Fabric ou détenir la certification Microsoft Fabric Data Engineer Associate (DP-700);
Added 53 mins ago
W
AI Engineer/Developer
W3Global
Toronto, ON
- $60,000 to $68,000 CAD / year
- Full-time
Required Skills: AWS, Lambda, API Gateway, CloudFormation/Terraform, Python/Java, Docker, Kubernetes, CI/CD, CloudWatch, Microservices.
Added 54 mins ago
SL
Principal Software Engineer, MarTech Platforms & Digital Enablement
Sun Life
Toronto, ON · Waterloo, ON · Sun Life Toronto Atria
- Full-time
Strong hands-on experience with: Java / Spring Boot / Python JavaScript / TypeScript APIs and Microservices Docker and Kubernetes
Added 1 hour ago
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Software Engineer - II
FISPAN
Vancouver, BC
- Full-time
We are looking for an experienced backend engineer who loves technology, can take ownership of the projects, is able to design and implement solutions to complex problems, feels proud of…
Added 1 hour ago
C
Senior Python Engineer
Citi
Mississauga, ON
- Full-time
Strong background in cloud platforms (AWS, Azure, GCP), including containerization (Docker) and contributing to Kubernetes orchestration.
Added 1 hour ago
VC
Staff Software Engineer
Valsoft Corporation
Remote, Canada
- Full-time
- Remote
We're hiring a Staff Software Engineer to own architecture and design decisions for our platform, including the modernization of legacy enterprise systems into modern, cloud-capable…
Added 1 hour ago
WT
Data Engineer
Wissen Technology
Montreal, QC
- Full-time
We are looking for a Data Engineer with strong backend engineering fundamentals and hands‑on experience building scalable, high‑performance data pipelines. The ideal candidate comes from a…
Added 1 hour ago
VT
AI Platform Developer
Volgo Technologies
Toronto, ON
- Contract
We are looking for a hands-on engineer who can build and deploy production-grade Agentic AI and multi-agent systems using Google ADK and MCP, while developing scalable AI platform…
Added 2 hours ago
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Technical Consultant (Data & AI)
Fastloop
Vancouver, BC
- Full-time
You aren’t just a “Data Engineer” or a “Software Engineer”; you are the “connective tissue” of modern intelligence. You will be responsible for the programmatic development of Agentic…
Added 2 hours ago
A
Forward Deployed Engineer – AI, Data Engineering & MLOps / Toronto, ON (Onsite) - FTE
AceStack
Toronto, ON
- Full-time
Job Title: Forward Deployed Engineer – AI, Data Engineering & MLOps
Added 2 hours ago
R
Python Java Sr Software Engineer -Montreal
RELX
Montreal, QC · Canada - Montreal (St. Laurent)
- Full-time
Beyond Python and Java experience, we work with the following technologies regularly: Confluent Kafka, Kubernetes, Linked-Data/RDF/JSON-LD, Databricks, Terraform, Github Actions, Apache…
Added 2 hours ago
E
Python Java Sr Software Engineer -Montreal
Elsevier
Montreal, QC · Canada - Montreal (St. Laurent)
- Full-time
Beyond Python and Java experience, we work with the following technologies regularly: Confluent Kafka, Kubernetes, Linked-Data/RDF/JSON-LD, Databricks, Terraform, Github Actions, Apache…
Added 3 hours ago
M
Lead Full Stack Software Engineer
Manulife
Toronto, ON · Waterloo, ON
- Full-time
As a Lead Full Stack Software Engineer, you will provide technical leadership across the software development lifecycle, partnering with product owners, architects, and engineering teams to…
Added 3 hours ago
HB
Software Engineer – Elite Quant - Up to $200,000 CAD Starting base + Exceptional benefits/bonus package Fund
Hunter Bond
Montreal, QC
- Full-time
My client - one of the world's leading quantitative trading firms - is hiring a Platform Engineer / Site Reliability Engineer (SRE) to design, build, and maintain highly scalable, resilient…
Added 3 hours ago
RE
Applied AI Engineer
Randstad Enterprise
Montreal, QC
- Contract
The Applied AI Engineer will work with business and technology teams to develop and implement Generative AI solutions. This is a hands-on engineering role focused on building prototypes,…
Added 3 hours 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 3 hours 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 3 hours ago
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Cloud Engineer - Early Career (Canada)
Jobright.ai
Canada
- Full-time
Jobright is your personal AI job search agent that transforms the way you do job search. They are seeking a Cloud Engineer to provision and manage cloud infrastructure, build CI/CD…
Added 3 hours ago
ZS
Forward Deployed Engineer
Zodiac Solutions, Inc
Toronto, ON
- Full-time
Hands-on experience with Git, Docker, Kubernetes, Airflow, MLflow, CI/CD, and distributed data processing frameworks.
Added 3 hours ago
TD
Robotics QA Automation Engineer
TELUS Digital
Canada
- Full-time
Knowledge of cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes).
Added 3 hours ago
DevOps & Cloud Platform Intern (December 2026 to April 2027)
ProCogia
Vancouver, BC
…infrastructure. You will work alongside our Cloud Platform Engineer on real engineering initiatives and learn how modern environments are designed, deployed, operated, and improved. You…

Tata Consultancy Services

Forward deployed Engineer

Toronto, ON, Canada

$100,000 to $120,000 CAD / year · Full-time

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Job details

Pay: $100,000 to $120,000 CAD / year
Job type: Full-time
Apply by: Nov 8, 2026
Posting language: English
Posted: Oct 9, 2026

Original job description

Inclusion without Exception

Tata Consultancy Services (TCS) is an equal opportunity employer, and embraces diversity in race, nationality, ethnicity, gender, age, physical ability, neurodiversity, and sexual orientation, to create a workforce that reflects the societies we operate in. Our continued commitment to Culture and Diversity is reflected in our people stories across our workforce and implemented through equitable workplace policies and processes.

Tata Consultancy Services (BSE: 532540, NSE: TCS) is the technology partner of choice for industry-leading organizations worldwide. Since its inception in 1968, TCS has upheld the highest standards of innovation, engineering excellence and customer service.

It has set an aspiration to become the world's largest AI-led technology services company and is enabling its clients to transform themselves across the full AI stack, from infrastructure to intelligence.

Rooted in the heritage of the Tata Group, TCS is focused on creating long term value for its clients, its investors, its employees, and the community at large. With a highly skilled workforce spread across 56 countries and 194 service delivery centers across the world, the company has been recognized as a top employer in six continents. With the ability to rapidly apply and scale new technologies, the company has built long term partnerships with its clients. Many of these relationships have endured into decades and navigated every technology cycle, from mainframes in the 1970s to artificial intelligence today.

Must-Have Technical / Functional Skills

Demonstrated experience in Data Engineering, AI Application Development, Cloud Data Platforms, and Production-grade Software Engineering, with a proven track record of delivering enterprise-scale solutions.
Strong hands-on expertise in Python, PySpark, SQL, REST APIs, Fast API, 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 Data Ops 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 subject matter experts, business users, and engineering teams through solution validation, production deployment, adoption, and handover.
Strong hands-on data discovery skills, including profiling unfamiliar 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 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 subject matter experts, 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.
Willingness and ability to travel or work onsite with stakeholders when an engagement requires close collaboration and accelerated delivery.

Roles & 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 landscapes, 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 stakeholders to deliver production-ready solutions.
Support solutioning, RFP responses, technical demonstrations, effort estimation, and 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 subject matter experts, product owners, and engineers for defined outcomes; map workflows, users, data, constraints, and decision points; and establish measurable success criteria.
Analyze data early to assess coverage, quality, volumes, distributions, edge cases, and process feasibility before committing to solution design and build scope.
Build working solutions quickly using real data and APIs, validate with users, and iteratively enhance for security, reliability, maintainability, and production operations.
Create evaluation datasets with subject matter experts, perform model and LLM error analysis, and recommend improvements.
Resolve data access, API, identity, network, security, infrastructure, and deployment blockers in collaboration with platform and engineering teams.
Own post-go-live stabilization by monitoring services, diagnosing failures, addressing latency and cost issues, executing recovery plans when required, and delivering fixes.
Measure adoption and business impact using usage data and agreed KPIs, and communicate outcomes through dashboards, demonstrations, and executive summaries.
Complete structured handovers with runbooks, support ownership documentation, knowledge transfer materials, reusable components, test artifacts, and deployment patterns.

Generic Managerial Skills

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 stakeholder environments.

Salary Range - CA$ 100,000 - CA$ 120,000 Per Year

TCS does not use artificial intelligence tools for candidate screening or evaluation. This post is for a current vacancy. The hiring process includes an initial screening, followed by a technical evaluation and managerial discussion.

Tata Consultancy Services Canada Inc. is committed to meeting the accessibility needs of all individuals in accordance with the Accessibility for Ontarians with Disabilities Act (AODA) and the Ontario Human Rights Code (OHRC). Should you require accommodation during the recruitment and selection process, please inform Human Resources.

Thank you for your interest in TCS. Candidates that meet the qualifications for this position will be contacted within a 2-week period. We invite you to continue to apply for other opportunities that match your profile.

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More about this job

Responsibilities

Design, build, and deploy enterprise AI and data applications, pipelines, and cloud solutions, including Claude-powered workflows, while ensuring security, reliability, performance, and cost efficiency. Work directly with stakeholders to validate solutions, lead production deployment and support, measure adoption and business impact, and provide technical leadership and handover.

Requirements

Requires demonstrated experience delivering enterprise-scale data engineering, AI applications, cloud data platforms, and production software, with hands-on expertise in Python, PySpark, SQL, APIs, RAG, MLOps/LLMOps, and modern engineering tools. A bachelor's degree in a related discipline is specified, along with BFSI experience, strong consulting and stakeholder skills, and the ability to work onsite or travel when needed.

Skills

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

Visa sponsorship

Not detected in the job text

Keywords

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

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