• Lead end-to-end implementation projects and ensure successful delivery • Facilitate discovery sessions and act as a trusted advisor to clients • Design scalable, thoughtful solution architectures aligned to business goals • Document and present solution designs for stakeholder approval • Oversee build activities and participate in hands-on configuration, as needed • Guide quality assurance and ensure high standards across deliverables • Lead client walkthroughs and support go-live activities

• Map the workflows in your domain — the ones running today, and the ones that don’t exist yet because they weren’t feasible without agents or automation tools. • Identify the step-change opportunities: where AI, ML, or automation unlock throughput, coverage, or speed. • Build the business case, quantify projected impact, and align with domain leadership on priorities. • Map structured and unstructured data flows across the systems involved (CRM, ERP, ticketing, document stores, internal tools, external SaaS). • Define the target workflow: what the agent does, what the human does, and where they hand off. • Figure out what context the agent or model needs to do the work well — and how to get it there reliably (retrieval, grounding, tool access, memory). • Design human-in-the-loop checkpoints so review adds value without becoming the bottleneck. • Stand up agents and automation pipelines using the organization’s approved AI platforms and frameworks. • Connect agents to business systems — via MCP servers, APIs, webhooks, CLIs, and skills — within the guardrails set by IT and security. • Configure tools, prompts, context, and retrieval pipelines so agents perform reliably on real work, not just in demos. • Handle integration gnarliness: auth, schema drift, rate limits, data quality, and the messy last-mile of enterprise systems. • Own agent performance end-to-end. Track the KPIs that matter — throughput, quality, cost, human intervention rate, cycle time, adoption. • Build and manage evals. Re-run them on any material model, data, or workflow change before it ships. • Triage failures, tune prompts and context, iterate on the workflow, and retire agents when they’re no longer the right tool. • Instrument observability: tracing, structured logs, dashboards.

Role Description We are seeking an experienced AI Solutions Architect / AI Engineering Advisor to lead the design, strategy, and deployment of Generative AI solutions on AWS. This is a highly consultative and stakeholder-facing role that combines deep technical expertise with strategic advisory responsibilities. The ideal candidate will serve as a trusted advisor to customer leadership teams, helping define AI roadmaps, governance frameworks, and scalable architectures while guiding the successful implementation of AI-powered applications. Key Responsibilities - Design and architect Generative AI solutions on AWS - Advise customer leadership on AI strategy, adoption, and governance - Build and deploy scalable AI applications leveraging Amazon Bedrock and foundation models - Design Retrieval-Augmented Generation (RAG) architectures - Implement embeddings and vector database solutions - Evaluate and recommend foundation models based on business requirements - Establish AI governance, security, and responsible AI best practices - Collaborate with engineering teams to operationalize AI solutions in production - Provide architectural guidance and technical leadership across AI initiatives Qualifications - 5+ years of experience in cloud architecture, AI/ML, software engineering, or related fields - Hands-on experience designing and deploying Generative AI solutions - Strong knowledge of Amazon Bedrock and AWS AI services - Experience with foundation models, prompt engineering, and LLM-based applications - Experience building Retrieval-Augmented Generation (RAG) solutions - Knowledge of embeddings and vector database technologies - Strong understanding of scalable cloud architectures and application deployment - Excellent communication and stakeholder management skills - Ability to engage with both technical teams and executive leadership Preferred Qualifications - AWS Certified Solutions Architect (Associate or Professional) - Experience advising enterprise customers on AI transformation initiatives - Knowledge of AI governance, risk management, and responsible AI frameworks - Experience leading AI strategy and architecture discussions with executive stakeholders - Background in machine learning, cloud-native application development, or data platforms Requirements - Candidates must be willing to undergo fingerprinting and a government background investigation (CJIS-type clearance process). - This position requires eligibility to work in the United States without current or future visa sponsorship. (Green Card holder)

Role Description We are looking for a professional and engaging Dynamics 365 Customer Engagement Solution Architect for our Data & Dynamics team to be based out of our Toronto, Vancouver, Edmonton, or Calgary branch! - Support Long View’s Business Applications and Data Modernization portfolio with assessments, solution design, and implementation of Microsoft Dynamics Customer Engagement/ Dynamics 365 solutions. - Map overall design to client requirements and systems, ensuring solutions align with business goals and processes, and fit within the enterprise context. - Participate with the implementation delivery team to develop a solution proposal that includes scope, assumptions, implementation plan, and technology solution options to meet project goals as well as longer-term needs. - Provide pre-sales technical assistance, demonstrations, and product education as required. - Develop estimates, Statements of Work (SOWs) and proposals that outline professional services required to meet client requirements. Qualifications - 5+ years of Microsoft Dynamics 365 Customer Engagement implementation experience with experience in other MS Dynamics modules. - 3+ years’ experience implementing and using Dynamics 365 CE Field Service/Microsoft CRM. - 3+ years of consulting experience. - Extensive experience with Microsoft Dataverse and Power Platform. - Experience using Azure DevOps for gathering and documenting business processes and requirements for the system with key business users. - Experience with SDK and 3rd party tools such as XRM Toolbox for the administration of Customer engagement system. - Knowledge in Dynamics 365 CE Field Service/Microsoft CRM and understanding of business processes. Requirements - Dynamics 365 Certifications such as Dynamics 365 Fundamentals. - Dynamics 365 for Field Service Functional Consultant. - Dynamics 365 for Customer Services Functional Consultant. - Dynamics 365 for Sales Functional Consultant. - Power Platform Fundamentals. - Power Platform Developer. Benefits - Great people and culture. - Comprehensive benefits plan. - Career Growth – Permanent staff positions, paid training, career life planning, and relocation and travel opportunities. - Interesting Work – Be part of exciting projects while accessing all the latest technologies. - Flexible Environment – A workplace that values the importance of flexibility for personal/professional growth, happiness, and wellness. - $122,360 - $150,000 a year Expected Salary Range plus 15% Variable earnings.