Toronto, Ontario M5V 3L9 Posted October 9th, 2026

Job Type: Full Time

Job Category: IT

Forward deployed Engineer

Location: Toronto, ON

Work Model: Onsite

Job Type: Full Time

Primary Skills

Python/PySpark, Claude & Agentic AI, SQL/APIs & MLOps

We are seeking an experienced Forward deployed Engineer with strong expertise in Data Engineering, AI application development, LLM integration, and MLOps. The ideal candidate will work closely with client stakeholders, business users, and engineering teams to design, build, deploy, and operationalize enterprise-grade AI and data solutions. This role combines hands-on software engineering, data discovery, solution architecture, rapid prototyping, and production ownership. The engineer will leverage Python, PySpark, SQL, Claude, REST APIs, RAG, and modern cloud data platforms to deliver scalable, secure, and measurable business outcomes.

Key Responsibilities

- Design, develop, and deploy enterprise-grade AI and data applications using Python, PySpark, Claude, SQL, REST APIs, and cloud data platforms.
- Collaborate with business and technology stakeholders to understand requirements, workflows, data landscapes, and delivery objectives.
- Define solution architecture, implementation roadmaps, and technical approaches aligned with business goals.
- Design and implement scalable batch, real-time, and streaming data pipelines.
- Build Claude-powered applications, copilots, and AI workflows using prompt engineering, RAG, vector databases, semantic search, and agentic AI patterns.
- Perform data discovery and profiling using Python, pandas, PySpark, and SQL to assess data quality, coverage, volumes, and business-process gaps.
- Develop rapid prototypes using real client data and APIs, validate solutions with business users, and iteratively prepare them for production.
- Implement and maintain CI/CD pipelines, automated testing, deployment automation, and infrastructure practices.
- Operationalize MLOps and LLMOps capabilities, including MLflow, model lifecycle management, monitoring, rollback, and production support.




- Apply responsible AI, security, privacy, governance, traceability, and human oversight controls.
- Troubleshoot data, API, identity, network, infrastructure, and deployment issues in collaboration with client teams.
- Create evaluation datasets, measure AI/LLM quality, conduct error analysis, and prioritize improvements.
- Monitor production services, resolve incidents, optimize performance and latency, and manage post-go-live stabilization.
- Measure user adoption and business impact using agreed KPIs, dashboards, and executive summaries.
- Develop reusable accelerators, reference architectures, engineering standards, runbooks, and implementation playbooks.
- Conduct client workshops, technical demonstrations, solution assessments, effort estimation, and RFP support.
- Mentor engineering teams and provide structured knowledge transfer and operational handover.

Required Skills & Experience

- 10–14 years of experience in Data Engineering, AI application development, cloud data platforms, APIs, and production-grade software engineering.
- Robust hands-on expertise in Python, PySpark, SQL, REST APIs, and FastAPI.
- Experience building AI-powered applications using Claude, prompt engineering, RAG, vector databases, semantic search, and agentic AI.
- Strong understanding of ETL/ELT, batch and streaming pipelines, data quality, metadata management, data lineage, observability, and DataOps.
- Hands-on experience with MLOps/LLMOps, MLflow, CI/CD, monitoring, deployment automation, and production support.
- Experience with Git, Docker, Kubernetes, Airflow, and distributed data processing frameworks.
- Knowledge of cloud infrastructure, data platforms,



orchestration, security, networking, monitoring, and cost optimization.
- Strong understanding of enterprise security, IAM/RBAC, encryption, secrets management, privacy, auditability, and compliance.
- Experience profiling unfamiliar datasets and assessing data quality, coverage, distributions, edge cases, and feasibility.
- Ability to rapidly prototype, validate, test, secure, and operationalize AI and data solutions.
- Experience creating evaluation datasets, analyzing model errors, and improving ML/LLM performance.
- Demonstrated ownership of production deployments, incident resolution, rollback, stabilization, and service reliability.
- Ability to translate business requirements into scalable technical solutions and measurable outcomes.
- Strong client-facing consulting, stakeholder management, workshop facilitation, and technical presentation skills.
- Experience working in Banking, Financial Services, or Insurance (BFSI) environments, with an understanding of regulatory and resilience requirements.
- Willingness to work onsite and travel when required for client engagements.
- Bachelor's degree in Computer Science, Engineering, Information Systems, Data Management, or a related discipline, or equivalent relevant experience.

Preferred Skills

- Cloud platform, Kubernetes, AI Engineering, MLOps, Data Engineering, Enterprise Architecture, Security, or Program Delivery certifications.
- Experience embedding with client teams in a forward-deployed delivery model.
- Experience measuring business outcomes such as time saved, error reduction, straight-through processing, and productivity improvements.
- Strong technical leadership, mentoring, architecture review, and engineering best-practice development skills.

Required Skills

Cloud Developer Cyber Vulnerability Management Analyst DevOps Engineer Fullstack Developer with GCP Mobile Architect Net Back Engineer NOC Network Engineer Office 365 Developer Web Development & Analytics Consultant

📌 Forward deployed Engineer (Toronto)
🏢 Realign
📍 Toronto