Forward Deployed Engineer (Python/Pyspark Developer)

Linuxassociation; Toronto; On-site; CAD 120,000 - 160,000; Full time

Job summary

Apptoza Inc. in Toronto, Ontario, is seeking a Senior Forward Deployed Engineer with deep Python and PySpark expertise to design, implement, and deploy data-driven AI solutions for enterprise clients.

You will embed with client teams, map complex workflows, and validate production-ready results using real data. The role combines production software engineering, data engineering, and AI application development with strong emphasis on client-facing delivery, cloud data platforms, and MLOps.

Qualifications

• Bachelor's degree in a relevant discipline.
• Experience delivering production-grade software and data engineering.
• Strong client-facing communication and consulting skills.

Responsibilities

• Embed with client SMEs, product owners, and engineers to map workflows and data flows.
• Prototype to production: define first useful release and success criteria.
• Profile client data using Python, PySpark, SQL to assess coverage, quality, and edge cases.
• Build thin working solutions with real client data and APIs; validate with users.
• Design and deploy enterprise AI/data apps using Python, PySpark, SQL, REST APIs, FastAPI, cloud data platforms.
• Develop Claude-powered apps, copilots, and AI workflows with prompt engineering, RAG, and vector databases.
• Design batch, real-time, and streaming data pipelines; integrate across enterprise systems.
• Implement MLOps/LLMOps: lifecycle management, CI/CD, monitoring, deployment automation, rollback.
• Handle data-access, API, identity, network, security, infra blockers with client teams.
• Own post-go-live monitoring, incident diagnosis, rollback, stabilization, latency, and cost optimization.
• Measure adoption and business impact via KPIs; handover with runbooks and knowledge transfer.

Skills

Python

PySpark

SQL

REST APIs

FastAPI

Git

Docker

Kubernetes

Airflow

MLflow

CI/CD

Distributed processing

MLOps

Claude

Prompt engineering

RAG

Vector databases

Semantic search

Agentic AI

Data engineering

Education

Bachelor's degree in a relevant discipline

Tools

Docker

Kubernetes

Airflow

MLflow

Git

Job description

# Forward Deployed Engineer (Python/Pyspark Developer)Apptoza Inc. · Toronto, Ontario, CABack to resultsForward Deployed Engineer (Python/Pyspark Developer)Apptoza Inc.Toronto, Ontario, CA Posted October 27, 2026 Via LinkedIn### Full Job DescriptionRole: Forward Deployed Engineer (Python/Pyspark Developer)TorontoFull timeThe opportunityWe are looking for a senior Forward Deployed Engineer who combines production-grade software engineering, data engineering, AI application development, and client-facing consulting. You will embed with business users, client SMEs, product owners, and engineering teams to understand complex workflows, rapidly validate solutions using real data, remove technical blockers, and own delivery through production launch, stabilization, adoption, and handover.What you will do• Embed with client SMEs, product owners, business users, and engineers to map workflows, users, data, constraints, and decision points.• Agree on the first useful release, measurable success criteria, and a practical roadmap from prototype to production.• Profile unfamiliar client data using Python, pandas, PySpark, and SQL to assess coverage, quality, volumes, distributions, edge cases, and feasibility.• Build thin working solutions using real client data and APIs, validate them with users, and iteratively harden them for production.• 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 and integrations 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 with client teams.• Own post-go-live monitoring, incident diagnosis, rollback, stabilization, latency, performance, reliability, and cost optimization.• Measure adoption and business impact using agreed KPIs, then complete structured handover with runbooks, support ownership, and knowledge transfer.What you bring• 10+ years of experience in data engineering, AI application development, cloud data platforms, and production software engineering.• Strong hands-on expertise in Python, PySpark, SQL, REST APIs, FastAPI, Git, Docker, Kubernetes, Airflow, MLflow, CI/CD, and distributed processing.• Experience with Claude, prompt engineering, RAG, vector databases, semantic search, and agentic AI patterns.• Strong knowledge 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 designs, define non-functional requirements, estimate effort, and drive implementation.• BFSI experience and strong client-facing skills across discovery, rapid prototyping, solution shaping, workshops, and technical presentations.• Bachelor's degree in a relevant discipline. Cloud, Kubernetes, AI engineering, MLOps, data engineering, architecture, or security certifications are preferred.