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Added 13 hours ago
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J&M Group
Toronto, ON
- Full-time

J&M Group

FORWARD DEPLOYEMENT ENGINEER

Canada

Full-time

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Job details

Job type: Full-time
Experience: 10+ years of experience in Data Engineering, AI Application Development, Cloud Data Platforms, and Production-grade Software Engineering.
Posting language: English
Posted: Oct 9, 2026

Original job description

Must Have Technical/Functional 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.
Willingness and ability to travel or work onsite with client teams when an engagement requires

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More about this job

Responsibilities

Design, build, and deploy production-ready data and AI applications, including pipelines, integrations, and MLOps/LLMOps capabilities. Work directly with client teams to discover and assess data, prototype and validate solutions, support production operations, and measure adoption and business impact.

Requirements

Requires 10+ years of experience across data engineering, AI application development, cloud data platforms, and production software engineering, with hands-on expertise in Python, PySpark, SQL, APIs, AI/LLM patterns, and modern data and cloud tools. Also requires BFSI experience, strong security and governance knowledge, client-facing consulting skills, and a bachelor's degree in a related discipline; relevant certifications are preferred.

Skills

Python
PySpark
SQL
REST APIs
FastAPI
AI Application Development
Retrieval-Augmented Generation
Vector Databases
Data Engineering
MLOps and LLMOps
Cloud Data Platforms
Kubernetes
Data Discovery
Enterprise Security and Governance
Client-Facing Consulting
Production Support

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 and Streaming Pipelines
DataOps
MLOps
LLMOps
MLflow
Git
Docker
Kubernetes
Airflow
CI/CD
Distributed Data Processing
Cloud Data Platforms
IAM/RBAC
Data Governance
BFSI
Data Profiling
Model Monitoring
Production Support

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