Technical Consultant I

Zafin•Toronto, ON

9d•$60,000 - $65,000•Hybrid

About The Position

Reporting to the Director, Technical Consulting, the Technical Consultant I will work across multiple client-facing projects to enable SaaS onboarding and successful client adoption of Zafin solutions. You will leverage modern cloud, integration, automation, and AI technologies to accelerate project delivery, improve onboarding experiences, and drive operational excellence. You will serve as the technical lead for SaaS onboarding initiatives, acting as a trusted advisor to clients and internal stakeholders. You will help define and implement scalable integration architectures, champion best practices across cloud platforms, and leverage AI-powered tools to improve solution design, documentation, testing, troubleshooting, and delivery outcomes. As a thought leader in integration and emerging AI-enabled delivery practices, you will collaborate with senior client technical leaders, product teams, and delivery organizations to ensure successful project execution from initiation through go-live and beyond. You will also contribute to product enhancements, develop automation and performance testing capabilities, and identify opportunities to apply AI and intelligent automation to improve delivery efficiency and client outcomes.

Requirements

Experience delivering at least one end-to-end SaaS implementation project.
Experience designing scalable end-to-end integration architectures.
Strong knowledge of application, data, and cloud integration patterns.
Deep understanding of API-first architectures and API-based integrations.
Strong understanding of network protocols, security architectures, and integration technologies.
Knowledge of integration frameworks commonly used by SaaS applications.
Experience creating architecture and solution designs using modeling tools.
Strong working knowledge of Azure, AWS, and/or GCP cloud platforms and integration services.
Experience with Kubernetes, Docker, PostgreSQL, and distributed application architectures.
Experience with clustering, scalability, and high-availability configurations.
Microsoft Azure Fundamentals certification or equivalent cloud knowledge.
5+ years of application and data integration experience.
Hands-on development experience with: Java, Spring Boot, Docker, Kubernetes, PostgreSQL
Strong problem-solving and analytical skills.
Ability to communicate complex technical concepts to technical and non-technical stakeholders.
Self-starter with an ownership mindset and passion for continuous improvement.
Experience working in Agile delivery environments.
Experience using AI-assisted development, testing, documentation, or productivity tools (e.g., GitHub Copilot, ChatGPT, Claude, Cursor, or similar).
Understanding of AI/LLM capabilities, limitations, and practical applications within software delivery and consulting.
Ability to identify opportunities for intelligent automation and AI-enabled process improvements.
Familiarity with AI governance, security, and responsible AI principles.
Degree in Computer Science, Engineering, or equivalent practical experience.

Nice To Haves

Experience with AI-powered software development and DevOps workflows.
Exposure to Generative AI, Retrieval-Augmented Generation (RAG), AI agents, or enterprise AI platforms.
Experience building integrations involving AI services and APIs.
Automation testing experience (JUnit or similar frameworks).
Application development experience in large enterprise IT environments.
Experience with Test-Driven Development (TDD) and Behavior-Driven Development (BDD).
Experience with observability and monitoring platforms.
Cloud certifications (Azure, AWS, or GCP).
Experience working in financial services or enterprise SaaS environments.

Responsibilities

Act as the primary technical consultant for SaaS onboarding and implementation projects.
Design and implement scalable, secure, and resilient integration architectures across cloud and hybrid environments.
Partner with customers and system integrators to define integration landscapes, technical requirements, and implementation roadmaps.
Translate complex technical and business requirements into actionable solution designs and delivery plans.
Present solution approaches to client technical leadership and drive alignment across stakeholders.
Develop a deep understanding of client business objectives and recommend innovative solutions that accelerate value realization.
Leverage AI-assisted development and productivity tools to accelerate solution delivery, troubleshooting, documentation, and testing activities.
Identify opportunities to automate onboarding, integration validation, deployment, monitoring, and support processes using AI and intelligent automation.
Utilize AI-powered analysis tools to improve root cause investigation, performance optimization, and operational efficiency.
Contribute to the adoption of AI best practices within consulting and delivery teams.
Evaluate emerging AI technologies and recommend practical applications that improve client and delivery outcomes.
Design end-to-end integration solutions leveraging APIs, event-driven architectures, messaging frameworks, and cloud-native integration services.
Define logical sequencing and execution plans for SaaS onboarding activities.
Collaborate with Product Engineering teams to implement recommended integration strategies and product enhancements.
Support cloud infrastructure, platform services, and system components required for successful integration.
Develop scripts, utilities, and automation frameworks to improve implementation quality and performance testing.
Contribute hands-on development using Java, Spring Boot, Docker, Kubernetes, PostgreSQL, and related technologies.
Improve onboarding experiences through enhanced processes, reusable assets, documentation, and automation.
Identify recurring delivery challenges and recommend scalable solutions.
Act as the voice of the customer internally to influence product, process, and documentation improvements.
Mentor team members on integration best practices, cloud technologies, and AI-enabled delivery approaches.
Lead the identification, isolation, resolution, and communication of technical issues within client environments.
Support performance tuning, scalability, availability, and resiliency initiatives.
Assist clients in establishing monitoring, observability, and operational best practices.