Forward Deployed Engineer (Python/PySpark + Claude)

Toronto, ON
On-site
Posted Oct 15, 2026
1 position

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Employment type: Full-time
Experience level: Senior · 5+ years
Minimum education: Bachelor’s degree
Posting language: English
Working hours: 40 hours per week
Seniority: Mid-Senior level
Application method: Direct apply is available

Job summary

Design, build, and deploy scalable AI applications, data pipelines, and enterprise integrations, including Claude-powered solutions using RAG, vector search, and agentic workflows. Lead client-facing delivery from prototyping through production support, monitoring, optimization, incident resolution, and measurement of business outcomes.

Job details

Position: Forward Deployed Engineer (Python/PySpark + Claude + SQL + APIs + Data & MLOps) Location: Toronto, ON (Onsite) Core Focus: AI Application Development, Data Engineering, LLMOps & Cloud Platforms Role Summary: We are seeking a hands-on Senior AI & Data Engineering professional to design, build, deploy, and support enterprise-grade AI and data solutions. The ideal candidate combines strong data engineering and software development skills with practical experience in Claude-powered AI applications, RAG, Agentic AI, cloud platforms, and production-grade MLOps/LLMOps. This role requires close client collaboration, rapid prototyping, technical leadership, and accountability for measurable business outcomes. Must-Have Technical Skills: Programming & APIs: Python, PySpark, SQL, REST APIs, FastAPI, pandas. AI & GenAI: Claude, Prompt Engineering, RAG, Vector Databases, Semantic Search, Agentic AI, AI Copilots. Data Engineering: ETL/ELT, batch and streaming pipelines, data quality, metadata, lineage, DataOps. MLOps/LLMOps: MLflow, Airflow, CI/CD, model lifecycle management, deployment automation, monitoring, evaluation, rollback. Cloud & DevOps: Cloud data platforms, Git, Docker, Kubernetes, distributed processing, infrastructure automation. Security & Governance: IAM/RBAC, encryption, secrets management, privacy, compliance, auditability, responsible AI. Enterprise Delivery: Solution architecture, production support, performance optimization, stakeholder management, and technical leadership. Key Responsibilities: Design and deliver scalable AI applications, data pipelines, and enterprise integrations. Build Claude-powered applications using RAG, prompt engineering, vector search, and agentic workflows. Translate business requirements into secure, reliable, cost-effective production solutions. Profile and validate unfamiliar client data; identify data-quality gaps, edge cases, and feasibility constraints. Rapidly prototype solutions using real client data and APIs, then harden them for production. Implement automated testing, CI/CD, monitoring, AI evaluation, security controls, and operational processes. Lead client workshops, solution design, technical presentations, and cross-functional engineering collaboration. Own post-go-live stabilization, incident resolution, performance tuning, and rollback when required. Measure adoption and business impact through KPIs; provide documentation, runbooks, and knowledge transfer. Preferred Background: Experience in Banking, Financial Services, or Insurance (BFSI). Strong client-facing consulting and forward-deployed delivery experience. Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field. Relevant cloud, AI/ML, Kubernetes, Data Engineering, or security certifications are preferred. Willingness to travel or work onsite with clients when required. Candidate Screening Priorities: Look for candidates who have personally delivered AI/GenAI solutions into production, demonstrated hands-on Python/PySpark/SQL and Claude/RAG experience, implemented MLOps/LLMOps, worked directly with client teams, and can demonstrate measurable business outcomes and post-production ownership. Important: If the engagement is classified as a regulated position, verify the applicable work-authorization requirements separately. The stated restrictions depend on the relevant regulation and client agreement.

What you’ll do

Requirements

Candidates should have hands-on experience delivering AI or GenAI solutions to production, with strong Python, PySpark, SQL, Claude/RAG, and MLOps/LLMOps capabilities. The role also calls for client-facing technical leadership, cloud and DevOps experience, and a bachelor's degree in a related field is preferred.