Senior Forward Deployed Engineer – AI & Data Engineering

# Senior Forward Deployed Engineer – AI & Data Engineering

📍 **Location:** Toronto, Ontario, Canada

🏢 **Work Model:** Hybrid

💰 **Pay Rate:** CAD $140–$180

📅 **Experience:** 10+ years

## About the Role

We are looking for a **Senior Forward Deployed Engineer** who combines production-grade software engineering, data engineering, AI application development, and client-facing consulting experience.

In this role, you will work closely with business users, client subject matter experts (SMEs), product owners, and engineering teams to understand complex business workflows, validate solutions using real client data, overcome technical challenges, and drive solutions from prototype to production launch.

You will own delivery through production deployment, stabilization, adoption, and handover.

## Key Responsibilities

• Work with client SMEs, product owners, business users, and engineering teams to understand and map workflows, users, data, constraints, and decision points.

• Define the first useful release, measurable success criteria, and a practical roadmap from prototype to production.

• Profile and analyze client data using **Python, pandas, PySpark, and SQL** to assess data quality, coverage, volume, distributions, edge cases, and feasibility.

• Build and validate working solutions using real client data and APIs, then enhance them for production readiness.

• Design, develop, and deploy enterprise AI and data applications using **Python, PySpark, SQL, REST APIs, FastAPI, and cloud data platforms**.

• Build Claude-powered applications, copilots, and AI workflows using prompt engineering, RAG, vector databases, semantic search, and agentic AI patterns.

• Design batch, real-time, and streaming data pipelines across enterprise systems.

• Implement **MLOps/LLMOps** capabilities, including lifecycle management, CI/CD, MLflow, monitoring, deployment automation, rollback, and production support.

• Create evaluation datasets with client SMEs, measure model and LLM quality, perform structured error analysis, and prioritize improvements.

• Resolve data access, API, identity, network, security, infrastructure, and deployment blockers.

• Own post-go-live monitoring, incident diagnosis, stabilization, performance, reliability, latency, and cost optimization.

• Measure adoption and business impact using agreed KPIs.

• Complete structured handovers with runbooks, support ownership, and knowledge transfer.

## Required Skills & Qualifications

• **10+ years of experience** in data engineering, AI application development, cloud data platforms, and production software engineering.

• Strong hands-on expertise in:

• Python and PySpark

• SQL and REST APIs

• FastAPI

• Git and Docker

• Kubernetes

• Airflow

• MLflow

• CI/CD

• Distributed processing

• Experience with **Claude, prompt engineering, RAG, vector databases, semantic search, and agentic AI patterns**.

• Strong understanding of ETL/ELT, batch and streaming pipelines, data quality, metadata, lineage, observability, and DataOps.

• Experience operationalizing **MLOps/LLMOps**, including model lifecycle management, automated deployment, monitoring, rollback, and production support.

• Knowledge of enterprise cloud services across compute, storage, integration, orchestration, networking, monitoring, security, and cost optimization.

• Understanding of IAM/RBAC, encryption, secrets management, privacy controls, auditability, compliance, and secure data access.

• Ability to translate business requirements into scalable technical designs, define non-functional requirements, estimate effort, and drive implementation.

• Strong client-facing communication and consulting skills.

## Preferred Qualifications

• **Banking and Financial Services (BFSI) domain experience**.

• Experience with client discovery, rapid prototyping, solution shaping, workshops, and technical presentations.

• Bachelor's degree in a relevant discipline.

• Certifications in cloud, Kubernetes, AI engineering, MLOps, data engineering, architecture, or security are preferred.

## Key Skills & Search Keywords

**Forward Deployed Engineer | AI Engineering | Data Engineering | Python | PySpark | SQL | FastAPI | REST APIs | Claude | Prompt Engineering | RAG | Vector Databases | Semantic Search | Agentic AI | MLOps | LLMOps | MLflow | Kubernetes | Docker | Airflow | CI/CD | ETL/ELT | Streaming Pipelines | Cloud Data Platforms | DataOps | BFSI**

## Ideal Candidate Profile

We are looking for a senior technical professional who can combine hands-on software and data engineering with AI application development and client-facing solution delivery. Candidates should be comfortable working with real enterprise data, rapidly building prototypes, deploying production-ready AI solutions, and owning post-launch outcomes.

## How to Apply

Please share your updated resume highlighting your experience in **Python, PySpark, SQL, AI application development, Claude, RAG, vector databases, MLOps/LLMOps, cloud platforms, and client-facing delivery**.