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.
