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Gather and document business requirements, translate them into user stories and acceptance criteria, map and optimize processes, and support CRM automation and customization in Creatio. Collaborate with clients and technical teams throughout agile delivery, validate solutions, analyze customer data, support adoption and training, resolve delivery issues, manage change control, and identify future consulting opportunities.

Gather and document business requirements, translate them into user stories and acceptance criteria, map and optimize customer workflows, and support CRM process automation. Configure Creatio using low-code tools, collaborate with technical teams, validate implementations, analyze customer data, and support client adoption, training, and onboarding. Participate in agile sprints, manage change control, identify future consulting opportunities, and deliver customer-focused solutions across enterprise client engagements.

Owns enterprise AI delivery engagements from discovery through weekly releases. Responsibilities include defining measurable outcomes, translating business problems into testable AI requirements, controlling scope on fixed-fee contracts, managing client stakeholders and domain experts, prioritizing backlogs, coordinating demos, tracking delivery health, and surfacing commercial risks. Requires product ownership or delivery experience, software shipping experience, AI literacy, executive presence, regulated-industry experience, Canadian work authorization, and willingness to travel.

Own enterprise client relationships, product scope, AI requirements, acceptance criteria, outcomes, and weekly release cadence. Lead discovery, backlog prioritization, stakeholder alignment, domain expert coordination, delivery health reporting, change adoption, and commercial risk management. The role requires shipping software in regulated industries, understanding LLM capabilities, managing fixed-fee engagements, and communicating with executive stakeholders.

Design and lead scalable data architectures across lakes, warehouses, analytics platforms, and cloud environments. Build data models, ETL/ELT pipelines, streaming ingestion solutions, and Databricks Lakehouse implementations. Ensure performance, reliability, governance, security, and privacy while advising clients on modernization strategies. Collaborate with stakeholders and analytics teams, translate business needs into technical solutions, mentor engineers, and provide technical leadership across data engineering projects.

Design and implement scalable data architectures, including lakes, warehouses, analytics platforms, and Databricks Lakehouse environments. Develop data models, ETL/ELT pipelines, streaming ingestion solutions, and integration frameworks. Lead data governance, security, compliance, performance optimization, migrations, and CI/CD implementation. Collaborate with clients and internal teams to translate business needs into technical solutions, advise on modernization strategies, and mentor data engineers.

Designs and leads scalable data architectures across cloud platforms, including data lakes, warehouses, analytics platforms, ETL/ELT pipelines, streaming ingestion, and data governance. Provides technical leadership, mentors engineers, optimizes performance and reliability, supports data migrations to Databricks Lakehouse, and advises clients on modernization and architecture decisions. Collaborates with stakeholders and analytics teams to deliver solutions for reporting, analytics, and AI initiatives.

Lead AI architecture across multiple enterprise client engagements, from pre-sales feasibility and technical scoping through production delivery. Govern model hosting, data residency, security, integrations, cost, latency, and reliability. Own reference architectures, accelerators, standards, and technical escalations while remaining hands-on with code and prototypes. Mentor GenAI and data engineers, review designs, support hiring, and represent the company before client architecture and security review boards.

Lead AI architecture across multiple client engagements, shaping solutions during pre-sales and governing designs through delivery. Define model hosting, security, data residency, integration, evaluation, observability, and cost standards. Maintain reference architectures and reusable accelerators, review code and designs, prototype solutions, mentor AI and data engineers, support technical hiring, and represent the company before enterprise architecture and security boards. The role requires hands-on enterprise software and production LLM experience, commercial judgment, and willingness to travel to Canadian client sites.

Design, build, and maintain C# APIs and web applications across modern and legacy .NET environments. Use AI-assisted development tools, implement integrations and security monitoring, modernize legacy systems, maintain automated regression tests, and collaborate on code reviews, CI/CD, and production releases. The role requires strong architecture experience, secure remote-work practices, and effective communication.